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Learning Vocabularies over a Fine Quantization A novel similarity measure for bag-of-words type large scale image retrieval is presented. The similarity function is learned in an unsupervised manner, requires no extra space over the standard bag-of-words method and is more discriminative than both L2-based soft assignm... | Spatial consistency of dense features within interest regions for efficient landmark recognition Recently, feature grouping has been proposed as a method for improving retrieval results for logos and web images. This relies on the idea that a group of features matching over a local region in an image is more discrimina... | Efficient Large-Scale Similarity Search Using Matrix Factorization We consider the image retrieval problem of finding the images in a dataset that are most similar to a query image. Our goal is to reduce the number of vector operations and memory for performing a search without sacrificing accuracy of the returned imag... | Image retrieval with reciprocal and shared nearest neighbors Content-based image retrieval systems typically rely on a similarity measure between image vector representations, such as in bag-of-words, to rank the database images in decreasing order of expected relevance to the query. However, the inherent asymmetry of ... | Fine-Grained Image Search Large-scale image search has been attracting lots of attention from both academic and commercial fields. The conventional bag-of-visual-words (BoVW) model with inverted index is verified efficient at retrieving near-duplicate images, but it is less capable of discovering fine-grained concepts ... | BSIFT: toward data-independent codebook for large scale image search. Bag-of-Words (BoWs) model based on Scale Invariant Feature Transform (SIFT) has been widely used in large-scale image retrieval applications. Feature quantization by vector quantization plays a crucial role in BoW model, which generates visual words ... | Total recall II: Query expansion revisited Most effective particular object and image retrieval approaches are based on the bag-of-words (BoW) model. All state-of-the-art retrieval results have been achieved by methods that include a query expansion that brings a significant boost in performance. We introduce three ext... | Improving image-based localization by active correspondence search We propose a powerful pipeline for determining the pose of a query image relative to a point cloud reconstruction of a large scene consisting of more than one million 3D points. The key component of our approach is an efficient and effective search meth... | Topology preserving hashing for similarity search Binary hashing has been widely used for efficient similarity search. Learning efficient codes has become a research focus and it is still a challenge. In many cases, the real-world data often lies on a low-dimensional manifold, which should be taken into account to capt... | BLOGS: Balanced local and global search for non-degenerate two view epipolar geometry This work considers the problem of estimating the epipolar geometry between two cameras without needing a prespecified set of correspondences. It is capable of resolving the epipolar geometry for cases when the views differ significan... | Meta-Recognition: The Theory and Practice of Recognition Score Analysis In this paper, we define meta-recognition, a performance prediction method for recognition algorithms, and examine the theoretical basis for its post-recognition score analysis form through the use of the statistical extreme value theory (EVT). The... | Comparative evaluation of Received Signal-Strength Index (RSSI) based indoor localization techniques for construction jobsites This paper evaluates the accuracy of several RSSI-based localization techniques on a live jobsite and compares them to results obtained in an operating building. RSSI-based localization algorit... | Training-Free, Generic Object Detection Using Locally Adaptive Regression Kernels We present a generic detection/localization algorithm capable of searching for a visual object of interest without training. The proposed method operates using a single example of an object of interest to find similar matches, does not re... | Calibration of Rotating Sensors This paper reports about a method for calibrating rotating senors, namely, rotating sensor-line cameras and laser range-finders. Both together are used to reconstruct accurately 3D environments, such as, for example, large buildings. One of the important steps in the 3D reconstruction pi... | 1.027572 | 0.025 | 0.015038 | 0.013044 | 0.006824 | 0.004822 | 0.002306 | 0.000972 | 0.000282 | 0.000073 | 0.00002 | 0.000003 | 0 | 0 |
Learning to Combine Mid-Level Cues for Object Proposal Generation In recent years, region proposals have replaced sliding windows in support of object recognition, offering more discriminating shape and appearance information through improved localization. One powerful approach for generating region proposals is based ... | Online Object Tracking with Proposal Selection Tracking-by-detection approaches are some of the most successful object trackers in recent years. Their success is largely determined by the detector model they learn initially and then update over time. However, under challenging conditions where an object can undergo tra... | Improving object detection with deep convolutional networks via Bayesian optimization and structured prediction Object detection systems based on the deep convolutional neural network (CNN) have recently made ground-breaking advances on several object detection benchmarks. While the features learned by these high-capac... | Object Detection via a Multi-region and Semantic Segmentation-Aware CNN Model. We propose an object detection system that relies on a multi-region deep convolutional neural network (CNN) that also encodes semantic segmentation-aware features. The resulting CNN-based representation aims at capturing a diverse set of dis... | Segmentation as selective search for object recognition For object recognition, the current state-of-the-art is based on exhaustive search. However, to enable the use of more expensive features and classifiers and thereby progress beyond the state-of-the-art, a selective search strategy is needed. Therefore, we adapt s... | Reduced Analytic Dependency Modeling: Robust Fusion for Visual Recognition This paper addresses the robustness issue of information fusion for visual recognition. Analyzing limitations in existing fusion methods, we discover two key factors affecting the performance and robustness of a fusion model under different data... | Lighting and pose robust face sketch synthesis Automatic face sketch synthesis has important applications in law enforcement and digital entertainment. Although great progress has been made in recent years, previous methods only work under well controlled conditions and often fail when there are variations of lighting ... | Action and Event Recognition with Fisher Vectors on a Compact Feature Set Action recognition in uncontrolled video is an important and challenging computer vision problem. Recent progress in this area is due to new local features and models that capture spatio-temporal structure between local features, or human-object ... | The feature and spatial covariant kernel: adding implicit spatial constraints to histogram In this paper, we are motivated to augment the holistic histogram representation with implicit spatial constrains. To be more concrete, we aim at finding a good match function for the problem of object/scene categorization which ... | Objects in Context In the task of visual object categorization, semantic con- text can play the very important role of reducing ambigu- ity in objects' visual appearance. In this work we propose to incorporate semantic object context as a post-processing step into any off-the-shelf object categorization model. Us- ing ... | Complex events detection using data-driven concepts Automatic event detection in a large collection of unconstrained videos is a challenging and important task. The key issue is to describe long complex video with high level semantic descriptors, which should find the regularity of events in the same category while dis... | Intelligent multi-camera video surveillance: A review Intelligent multi-camera video surveillance is a multidisciplinary field related to computer vision, pattern recognition, signal processing, communication, embedded computing and image sensors. This paper reviews the recent development of relevant technologies from ... | A Parallel Hardware Architecture for Scale and Rotation Invariant Feature Detection This paper proposes a parallel hardware architecture for image feature detection based on the scale invariant feature transform algorithm and applied to the simultaneous localization and mapping problem. The work also proposes specific ... | Keypoint Detection Based on the Unimodality Test of HOGs. We present a new method for keypoint detection. The main drawback of existing methods is their lack of robustness to image distortions. Small variations of the image lead to big differences in keypoint localizations. The present work shows a way of determining s... | 1.203888 | 0.101944 | 0.026213 | 0.01938 | 0.004731 | 0.000974 | 0.000244 | 0.000075 | 0.000018 | 0.000001 | 0 | 0 | 0 | 0 |
3D Object Recognition in Cluttered Scenes with Local Surface Features: A Survey 3D object recognition in cluttered scenes is a rapidly growing research area. Based on the used types of features, 3D object recognition methods can broadly be divided into two categories-global or local feature based methods. Intensive res... | A Novel Multi-Purpose Matching Representation of Local 3D Surfaces: A Rotationally Invariant, Efficient, and Highly Discriminative Approach With an Adjustable Sensitivity In this paper, a novel approach to local 3D surface matching representation suitable for a range of 3D vision applications is introduced. Local 3D su... | Difference of Normals as a Multi-scale Operator in Unorganized Point Clouds A novel multi-scale operator for unorganized 3D point clouds is introduced. The Difference of Normals (DoN) provides a computationally efficient, multi-scale approach to processing large unorganized 3D point clouds. The application of DoN in th... | Aligning 2.5D Scene Fragments With Distinctive Local Geometric Features and Voting-Based Correspondences Aligning 2.5D views has been extensively explored in the past decades, where most prior works have concentrated on object data with complex structures. This paper presents a method to align real-word scene scans wit... | Variable Dimensional Local Shape Descriptors for Object Recognition in Range Data We propose a new set of highly descriptive local shape descriptors (LSDs) for model-based object recognition and pose determination in input range data. Object recognition is performed in three phases: point matching, where point correspo... | Voting-Based Pose Estimation For Robotic Assembly Using A 3d Sensor We propose a voting-based pose estimation algorithm applicable to 3D sensors, which are fast replacing their 2D counterparts in many robotics, computer vision, and gaming applications. It was recently shown that a pair of oriented 3D points, which are ... | Harris 3D: a robust extension of the Harris operator for interest point detection on 3D meshes With the increasing amount of 3D data and the ability of capture devices to produce low-cost multimedia data, the capability to select relevant information has become an interesting research field. In 3D objects, the aim is t... | Comparing images using the Hausdorff distance The Hausdorff distance measures the extent to which each point of a model set lies near some point of an image set and vice versa. Thus, this distance can be used to determine the degree of resemblance between two objects that are superimposed on one another. Efficient algo... | Reconstructing a textured CAD model of an urban environment using vehicle-borne laser range scanners and line cameras Abstract. In this paper, a novel method is presented for generating a textured CAD model of an outdoor urban environment using a vehicle-borne sensor system. In data measurement, three single-row laser ... | The MOPED framework: Object recognition and pose estimation for manipulation We present MOPED, a framework for Multiple Object Pose Estimation and Detection that seamlessly integrates single-image and multi-image object recognition and pose estimation in one optimized, robust, and scalable framework. We address two mai... | Modeling the World from Internet Photo Collections There are billions of photographs on the Internet, comprising the largest and most diverse photo collection ever assembled. How can computer vision researchers exploit this imagery? This paper explores this question from the standpoint of 3D scene modeling and visualiz... | Simultaneous Camera Pose and Correspondence Estimation with Motion Coherence Traditionally, the camera pose recovery problem has been formulated as one of estimating the optimal camera pose given a set of point correspondences. This critically depends on the accuracy of the point correspondences and would have problems... | A Dense Stereo Matching Using Two-Pass Dynamic Programming with Generalized Ground Control Points A method for solving dense stereo matching problem is presented in this paper. First, a new generalized ground control points (GGCPs) scheme is introduced, where one or more disparity candidates for the true disparity of e... | Mixture Distributions for Weakly Supervised Classification in Remote Sensing Images For its simplicity and efficiency, the bag-of-words represe ntation based on appearance features is widely used in image and text classifi cation. Its draw- back is that shape patterns of the image are neglected. This paper presents a n... | 1.015616 | 0.015714 | 0.014286 | 0.011825 | 0.00908 | 0.005714 | 0.002454 | 0.000324 | 0.000084 | 0.000023 | 0.000005 | 0 | 0 | 0 |
The method for image retrieval based on multi-factors correlation utilizing block truncation coding. In this paper, we proposed multi-factors correlation (MFC) to describe the image, structure element correlation (SEC), gradient value correlation (GVC) and gradient direction correlation (GDC). At first, the RGB color s... | A novel method for image retrieval based on structure elements' descriptor In this paper, structure elements' descriptor (SED) - a novel texture descriptor, is proposed. SED can effectively describe images and represent image local features. Moreover, SED can extract and describe color and texture features. The image s... | Visual word spatial arrangement for image retrieval and classification We present word spatial arrangement (WSA), an approach to represent the spatial arrangement of visual words under the bag-of-visual-words model. It lies in a simple idea which encodes the relative position of visual words by splitting the image spac... | Image retrieval based on multi-texton histogram This paper presents a novel image feature representation method, called multi-texton histogram (MTH), for image retrieval. MTH integrates the advantages of co-occurrence matrix and histogram by representing the attribute of co-occurrence matrix using histogram. It can be ... | Histograms of Oriented Gradients for Human Detection We study the question of feature sets for robust visual object recognition, adopting linear SVM based human detection as a test case. After reviewing existing edge and gradient based descriptors, we show experimentally that grids of Histograms of Oriented Gradient (H... | Photorealistic Scene Reconstruction by Voxel Coloring A novel scene reconstruction technique is presented,different from previous approaches in its ability to copewith large changes in visibility and its modeling of intrinsicscene color and texture information. The methodavoids image correspondence problems by working ... | Surface reconstruction from unorganized points We describe and demonstrate an algorithm that takes as input an unorganized set of points 1 n IR 3 on or near an un- known manifold M, and produces as output a simplicial surface that approximates M. Neither the topology, the presence of boundaries, nor the geometry of M a... | Human recognition using 3D ear images. This paper proposes an ear recognition technique which makes use of 3D along with co-registered 2D ear images. It presents a two-step matching technique to compare two 3D ears. In the first step, it computes salient 3D data points from 3D ear images with the help of local 2D featu... | Video Stabilization Using Scale-Invariant Features Video Stabilization is one of those important video processing techniques to remove the unwanted camera vibration in a video sequence. In this paper, we present a practical method to remove the annoying shaky motion and reconstruct a stabilized video sequence with good... | Epipolar Geometry of Panoramic Cameras . This paper presents fundamental theory and design of centralpanoramic cameras. Panoramic cameras combine a convex hyperbolic orparabolic mirror with a perspective camera to obtain a large field of view.We show how to design a panoramic camera with a tractable geometryand we pro... | Learning to detect unseen object classes by between-class attribute transfer We study the problem of object classification when train- ing and test classes are disjoint, i.e. no training examples of the target classes are available. This setup has hardly been studied in computer vision research, but it is the rule rath... | IrisNet: an internet-scale architecture for multimedia sensors Most current sensor network research explores the use of extremely simple sensors on small devices called motes and focuses on over-coming the resource constraints of these devices. In contrast, our research explores the challenges of multimedia sensors and... | Complex events detection using data-driven concepts Automatic event detection in a large collection of unconstrained videos is a challenging and important task. The key issue is to describe long complex video with high level semantic descriptors, which should find the regularity of events in the same category while dis... | Autonomous Detection Of Volcanic Plumes On Outer Planetary Bodies We experimentally evaluated the efficacy of various autonomous supervised classification techniques for detecting transient geophysical phenomena. We demonstrated methods of detecting volcanic plumes on the planetary satellites Io and Enceladus using spa... | 1.1 | 0.033333 | 0.011111 | 0.006667 | 0.000068 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Internet image archaeology: automatically tracing the manipulation history of photographs on the web We propose a system for automatically detecting the ways in which images have been copied and edited or manipulated. We draw upon these manipulation cues to construct probable parent-child relationships between pairs of... | Exploitation and Exploration Balanced Hierarchical Summary For Landmark Images While we have made significant progress over image understanding and search, how to meet the ultimate goal of satisfying both exploration and exploitation in one single system is still an open challenge. In the context of landmark images, it... | Partial-Duplicate Clustering and Visual Pattern Discovery on Web Scale Image Database In this paper, we study the problem of discovering visual patterns and partial-duplicate images, which is fundamental to visual concept representation and image parsing, but very challenging when the database is extremely large, such ... | An efficient near-duplicate video shot detection method using shot-based interest points We propose a shot-based interest point selection approach for effective and efficient near-duplicate search over a large collection of video shots. The basic idea is to eliminate the local descriptors with lower frequencies among t... | Partition min-hash for partial duplicate image discovery In this paper, we propose Partition min-Hash (PmH), a novel hashing scheme for discovering partial duplicate images from a large database. Unlike the standard min-Hash algorithm that assumes a bag of words image representation, our approach utilizes the fact that... | Scalable logo recognition in real-world images In this paper we propose a highly effective and scalable framework for recognizing logos in images. At the core of our approach lays a method for encoding and indexing the relative spatial layout of local features detected in the logo images. Based on the analysis of the l... | An Image-Based Approach to Video Copy Detection With Spatio-Temporal Post-Filtering This paper introduces a video copy detection system which efficiently matches individual frames and then verifies their spatio-temporal consistency. The approach for matching frames relies on a recent local feature indexing method, whic... | Object Retrieval With Large Vocabularies And Fast Spatial Matching In this paper, we present a large-scale object retrieval system. The user supplies a query object by selecting a region of a query image, and the system returns a ranked list of images that contain the same object, retrieved from a large corpus. We demo... | Detecting Irregularities in Images and in Video We address the problem of detecting irregularities in visual data, e.g., detecting suspicious behaviors in video sequences, or identifying salient patterns in images. The term "irregular" depends on the context in which the "regular" or "valid" are defined. Yet, it is not... | Nested sparse quantization for efficient feature coding Many state-of-the-art methods in object recognition extract features from an image and encode them, followed by a pooling step and classification. Within this processing pipeline, often the encoding step is the bottleneck, for both computational efficiency and per... | Online multiclass learning by interclass hypothesis sharing We describe a general framework for online multiclass learning based on the notion of hypothesis sharing. In our framework sets of classes are associated with hypotheses. Thus, all classes within a given set share the same hypothesis. This framework includes a... | Efficient Image Feature Combination with Hierarchical Scheme for Content-Based Image Management System This paper proposes efficient image feature combinations based on local descriptor and hierarchical indexing scheme obtained by clustering with global descriptor for content-based image management system such as image... | 3d Indoor Environment Modeling By A Mobile Robot With Omnidirectional Stereo And Laser Range Finder This paper deals with generation of 3D environment models. The model is expected to be used for location recognition by robots and users. For such a use, very precise models are not necessary. We therefore develop a meth... | Has somethong changed here? Autonomous difference detection for security patrol robots This paper presents a system for autonomous change detection with a security patrol robot. In an initial step a reference model of the environment is created and changes are then detected with respect to the reference model as differ... | 1.046133 | 0.028571 | 0.028571 | 0.014311 | 0.00898 | 0.003308 | 0.001085 | 0.000134 | 0.00001 | 0 | 0 | 0 | 0 | 0 |
Incremental algorithms for finding the convex hulls of circles and the lower envelopes of parabolas : The existing O(n log n) algorithms for finding the convex hulls of circlesand the lower envelope of parabolas follow the divide-and-conquer paradigm. Thedifficulty with developing incremental algorithms for these prob... | Fast Algorithms for Large-State-Space HMMs with Applications to Web Usage Analysis In applying Hidden Markov Models to the analysis of massive data streams, it is often necessary to use an artificially reduced set of states; this is due in large part to the fact that the basic HMM estimation algorithms have a quadratic... | Multiresolution Markov models for signal and image processing Reviews a significant component of the rich field of statistical multiresolution (MR) modeling and processing. These MR methods have found application and permeated the literature of a widely scattered set of disciplines, and one of our principal objectives ... | Distance transformations in digital images A distance transformation converts a binary digital image, consisting of feature and non-feature pixels, into an image where all non-feature pixels have a value corresponding to the distance to the nearest feature pixel. Computing these distances is in principle a global opera... | Comparison of Graph Cuts with Belief Propagation for Stereo, using Identical MRF Parameters Recent stereo algorithms have achieved impressive resultsby modelling the disparity image as a Markov RandomField (MRF). An important component of an MRF-basedapproach is the inference algorithm used to find the mostlikely setti... | Segmentation Based Disparity Estimation Using Color And Depth Information The well-known cooperative stereo uses two dimensional rectangular window for a local block matching and three dimensional box-shaped volume for a global optimization procedure. In many cases. appropriate selections of these matching regions call... | A fusion method of data association and virtual detection for minimizing track loss and false track In this paper, we present a method to track multiple moving vehicles using the global nearest neighborhood (GNN) data association (DA) based on 2D global position and virtual detection based on motion tracking. Unlikely ... | Real-time stereo matching based on fast belief propagation. In this paper, a global optimum stereo matching algorithm based on improved belief propagation is presented which is demonstrated to generate high quality results while maintaining real-time performance. These results are achieved using a foundation based on t... | Fast unambiguous stereo matching using reliability-based dynamic programming. An efficient unambiguous stereo matching technique is presented in this paper. Our main contribution is to introduce a new reliability measure to dynamic programming approaches in general. For stereo vision application, the reliability of a p... | Real-time stereo on GPGPU using progressive multi-resolution adaptive windows We introduce a new GPGPU-based real-time dense stereo matching algorithm. The algorithm is based on a progressive multi-resolution pipeline which includes background modeling and dense matching with adaptive windows. For applications in which... | Design, Architecture and Control of a Mobile Site-Modeling Robot A distributed, modular, heterogeneous architecture is presented that illustrates an approach to solving and integrating common tasks in mobile robotics, such as path planning, localization, sensor fusion, environmental modeling, and motion control. Experi... | Shape-Based Object Localization for Descriptive Classification Discriminative tasks, including object categorization and detection, are central components of high-level computer vision. However, sometimes we are interested in a finer-grained characterization of the object's properties, such as its pose or articulation.... | Multiscale Keypoint Analysis based on Complex Wavelets | Video Snapshots: Creating High-Quality Images from Video Clips. We describe a unified framework for generating a single high-quality still image ("snapshot") from a short video clip. Our system allows the user to specify the desired operations for creating the output image, such as super-resolution, noise and blur redu... | 1.075017 | 0.025022 | 0.017401 | 0.009531 | 0.001721 | 0.000046 | 0.000026 | 0.000017 | 0.000011 | 0.000005 | 0.000001 | 0 | 0 | 0 |
A fast dual method for HIK SVM learning Histograms are used in almost every aspect of computer vision, from visual descriptors to image representations. Histogram Intersection Kernel (HIK) and SVM classifiers are shown to be very effective in dealing with histograms. This paper presents three contributions concerning H... | Efficient and Effective Visual Codebook Generation Using Additive Kernels Common visual codebook generation methods used in a bag of visual words model, for example, k-means or Gaussian Mixture Model, use the Euclidean distance to cluster features into visual code words. However, most popular visual descriptors are his... | Combining color-based invariant gradient detector with HoG descriptors for robust image detection in scenes under cast shadows In this work we present a robust detection method in outdoor scenes under cast shadows using color based invariant gradients in combination with HoG local features. The method achieves good det... | Large-scale image categorization with explicit data embedding Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel machines are difficult to scale to large training sets, it has been proposed to... | Learning and using taxonomies for fast visual categorization The computational complexity of current visual categorization algorithms scales linearly at best with the number of categories. The goal of classifying simultaneously Ncat = 104 - 105 visual categories requires sub-linear classification costs. We explore algo... | Kernel Codebooks for Scene Categorization This paper introduces a method for scene categorization by modeling ambiguity in the popular codebook approach. The codebook
approach describes an image as a bag of discrete visual codewords, where the frequency distributions of these words are used
for image categorization. ... | Performance evaluation of local colour invariants In this paper, we compare local colour descriptors to grey-value descriptors. We adopt the evaluation framework of Mikolayzcyk and Schmid. We modify the framework in several ways. We decompose the evaluation framework to the level of local grey-value invariants on which... | Estimating the number of people in crowded scenes by MID based foreground segmentation and head-shoulder detection This paper proposes a novel method to address the problem of estimating the number of people in surveillance scenes with people gathering and waiting. The proposed method combines a MID (mosaic image diffe... | Scene recognition on the semantic manifold A new architecture, denoted spatial pyramid matching on the semantic manifold (SPMSM), is proposed for scene recognition. SPMSM is based on a recent image representation on a semantic probability simplex, which is now augmented with a rough encoding of spatial information. A c... | Good Practice in Large-Scale Learning for Image Classification We benchmark several SVM objective functions for large-scale image classification. We consider one-versus-rest, multiclass, ranking, and weighted approximate ranking SVMs. A comparison of online and batch methods for optimizing the objectives shows that onl... | Learning visual object definitions by observing human activities Humanoid robots, while moving in our everyday environments, necessarily need to recognize objects. Providing robust object definitions for every single object in our environ- ments is challenging and impossible in practice. In this work, we build upon the... | Autonomous visual navigation of a mobile robot using a human-guided experience Information on the surrounding environment is necessary for a robot to move autonomously. Many previous robots use a given map and landmarks. Making such a map is, however, a tedious work for the user. Therefore this paper proposes a navigat... | Recognizing complex events using large margin joint low-level event model In this paper we address the challenging problem of complex event recognition by using low-level events. In this problem, each complex event is captured by a long video in which several low-level events happen. The dataset contains several videos... | Hybrid social media network Analysis and recommendation of multimedia information can be greatly improved if we know the interactions between the content, user, and concept, which can be easily observed from the social media networks. However, there are many heterogeneous entities and relations in such networks, making... | 1.028877 | 0.030303 | 0.018182 | 0.005062 | 0.003306 | 0.001222 | 0.000319 | 0.000107 | 0.000016 | 0.000002 | 0 | 0 | 0 | 0 |
Minimum correspondence sets for improving large-scale augmented paper Augmented Paper (AP) is an important area of Augmented Reality (AR). Many AP systems rely on visual features for paper document identification. Although promising, these systems can hardly support large sets of documents (i.e. one million documents) ... | A tool for authoring unambiguous links from printed content to digital media Embedded Media Markers (EMMs) are nearly transparent icons printed on paper documents that link to associated digital media. By using the document content for retrieval, EMMs are less visually intrusive than barcodes and other glyphs while sti... | Embedded media barcode links: optimally blended barcode overlay on paper for linking to associated media Embedded Media Barcode Links, or simply EMBLs, are optimally blended iconic barcode marks, printed on paper documents, that signify the existence of multimedia associated with that part of the document content (Figu... | Embedded media markers: marks on paper that signify associated media Embedded Media Markers, or simply EMMs, are nearly transparent iconic marks printed on paper documents that signify the existence of media associated with that part of the document. EMMs also guide users' camera operations for media retrieval. Users t... | Distinctive Image Features from Scale-Invariant Keypoints This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene. The features are invariant to image scale and rotation, and are shown to provide r... | A flexible new technique for camera calibration We propose a flexible technique to easily calibrate a camera. It only requires the camera to observe a planar pattern shown at a few (at least two) different orientations. Either the camera or the planar pattern can be freely moved. The motion need not be known. Radial le... | A conference key distribution system Encryption is used in a communication system to safeguard information in the transmitted messages from anyone other than the intended receiver(s). To perform the encryption and decryption the transmitter and receiver(s) ought to have matching encryption and decryption keys. A clever... | Human recognition using 3D ear images. This paper proposes an ear recognition technique which makes use of 3D along with co-registered 2D ear images. It presents a two-step matching technique to compare two 3D ears. In the first step, it computes salient 3D data points from 3D ear images with the help of local 2D featu... | Object tracking: A survey The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends. Object tracking, in general, is a challenging problem. Difficulties in tracking objects can arise due to abrupt object motion, changing appearance patt... | ITEMS: intelligent travel experience management system An intelligent travel experience management system, abbreviated as ITEMS, is proposed to help tourists organize and present the digital travel contents in an automatic and efficient manner. Readily available metadata are adopted to reduce the overhead of user inter... | High-quality passive facial performance capture using anchor frames We present a new technique for passive and markerless facial performance capture based on anchor frames. Our method starts with high resolution per-frame geometry acquisition using state-of-the-art stereo reconstruction, and proceeds to establish a sin... | Minimal correlation classification When the description of the visual data is rich and consists of many features, a classification based on a single model can often be enhanced using an ensemble of models. We suggest a new ensemble learning method that encourages the base classifiers to learn different aspects of the d... | Integrating Representative and Discriminative Models for Object Category Detection We propose a novel approach for shape-based segmentation based on a specially designed level set function format. This format permits us to better control the process of object registration which is an important part in the shapebased se... | Boosting k-NN for Categorization of Natural Scenes The k-nearest neighbors (k-NN) classification rule has proven extremely successful in countless many computer vision applications. For example, image categorization often relies on uniform voting among the nearest prototypes in the space of descriptors. In spite of its... | 1.2 | 0.2 | 0.1 | 0.022222 | 0.000017 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Mobile product image search by automatic query object extraction Mobile product image search aims at identifying a product, or retrieving similar products from a database based on a photo captured from a mobile phone camera. Application of traditional image retrieval methods (e.g. bag-of-words) to mobile visual search ... | Recognizing Products: A Per-Exemplar Multi-Label Image Classification Approach Large-scale instance-level image retrieval aims at retrieving specific instances of objects or scenes. Simultaneously retrieving multiple objects in a test image adds to the difficulty of the problem, especially if the objects are visually s... | Scalable Face Image Retrieval with Identity-Based Quantization and Multireference Reranking State-of-the-art image retrieval systems achieve scalability by using a bag-of-words representation and textual retrieval methods, but their performance degrades quickly in the face image domain, mainly because they produce visu... | Robust Text Detection In Natural Images With Edge-Enhanced Maximally Stable Extremal Regions Detecting text in natural images is an important prerequisite. In this paper, we propose a novel text detection algorithm, which employs edge-enhanced Maximally Stable Extremal Regions as basic letter candidates. These candidat... | Associative Hierarchical Random Fields This paper makes two contributions: the first is the proposal of a new model—The associative hierarchical random field (AHRF), and a novel algorithm for its optimization; the second is the application of this model to the problem of semantic segmentation. Most methods for semantic... | Unsupervised discovery of co-occurrence in sparse high dimensional data An efficient min-Hash based algorithm for discovery of dependencies in sparse high-dimensional data is presented. The dependencies are represented by sets of features co-occurring with high probability and are called co-ocsets.Sparse high dimension... | Unsupervised discovery of mid-level discriminative patches The goal of this paper is to discover a set of discriminative patches which can serve as a fully unsupervised mid-level visual representation. The desired patches need to satisfy two requirements: 1) to be representative, they need to occur frequently enough in... | Learning Where To Classify In Multi-View Semantic Segmentation There is an increasing interest in semantically annotated 3D models, e.g. of cities. The typical approaches start with the semantic labelling of all the images used for the 3D model. Such labelling tends to be very time consuming though. The inherent redund... | Latent Semantic Minimal Hashing for Image Retrieval. Hashing-based similarity search is an important technique for large-scale query-by-example image retrieval system, since it provides fast search with computation and memory efficiency. However, it is a challenge work to design compact codes to represent original feat... | Distinctive Image Features from Scale-Invariant Keypoints This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene. The features are invariant to image scale and rotation, and are shown to provide r... | A Multi-State Constraint Kalman Filter For Vision-Aided Inertial Navigation In this paper, we present an Extended Kalman Filter (EKF)-based algorithm for real-time vision-aided inertial navigation. The primary contribution of this work is the derivation of a measurement model that is able to express the geometric const... | A new approach for fingerprint verification based on wide baseline matching using local interest points and descriptors In this article is proposed a new approach to automatic fingerprint verification that is not based on the standard ridge-minutiae-based framework, but in a general-purpose wide baseline matching metho... | Panoramic Depth Imaging: Single Standard Camera Approach In this paper we present a panoramic depth imaging system. The system is mosaic-based which means that we use a single rotating camera and assemble the captured images in a mosaic. Due to a setoff of the camera's optical center from the rotational center of the s... | Ghost detection and removal for high dynamic range images: Recent advances High dynamic range (HDR) image generation and display technologies are becoming increasingly popular in various applications. A standard and commonly used approach to obtain an HDR image is the multiple exposures' fusion technique which consists... | 1.030905 | 0.018514 | 0.014785 | 0.007086 | 0.004541 | 0.001869 | 0.000878 | 0.000344 | 0.000107 | 0.000023 | 0.000004 | 0 | 0 | 0 |
Modeling Coverage in Camera Networks: A Survey Modeling the coverage of a sensor network is an important step in a number of design and optimization techniques. The nature of vision sensors presents unique challenges in deriving such models for camera networks. A comprehensive survey of geometric and topological covera... | Evaluating the fuzzy coverage model for 3D multi-camera network applications An intuitive three-dimensional task-oriented coverage model for 3D multi-camera networks based on fuzzy sets is presented. The model captures the vagueness inherent in the concept of visual coverage, with a specific target of the feature detec... | Visual coverage using autonomous mobile robots for search and rescue applications. This paper focuses on visual sensing of 3D large-scale environments. Specifically, we consider a setting where a group of robots equipped with a camera must fully cover a surrounding area. To address this problem we propose a novel descr... | Leveraging 3D City Models for Rotation Invariant Place-of-Interest Recognition Given a cell phone image of a building we address the problem of place-of-interest recognition in urban scenarios. Here, we go beyond what has been shown in earlier approaches by exploiting the nowadays often available 3D building informatio... | A randomized art-gallery algorithm for sensor placement This paper descirbes a placement strategy to compute a set of “good” locations where visual sensing will be most effective. Throughout this paper it is assumed that a {\em polygonal 2-D map} of a workspace is given as input. This polygonal map --- also known as a ... | Determining an initial image pair for fixing the scale of a 3d reconstruction from an image sequence Algorithms for metric 3d reconstruction of scenes from calibrated image sequences always require an initialization phase for fixing the scale of the reconstruction. Usually this is done by selecting two frames from the ... | Scene Summarization for Online Image Collections We formulate the problem of scene summarization as se- lecting a set of images that efficiently represents the visual content of a given scene. The ideal summary presents the most interesting and important aspects of the scene with minimal redundancy. We propose a soluti... | A survey of glove-based input Clumsy intermediary devices constrain our interaction with computers and their applications. Glove-based input devices let us apply our manual dexterity to the task. We provide a basis for understanding the field by describing key hand-tracking technologies and applications using glove-bas... | Comparing images using the Hausdorff distance The Hausdorff distance measures the extent to which each point of a model set lies near some point of an image set and vice versa. Thus, this distance can be used to determine the degree of resemblance between two objects that are superimposed on one another. Efficient algo... | Part-based statistical models for object classification and detection We propose using simple mixture models to define a set of mid-level binary local features based on binary oriented edge input. The features capture natural local structures in the data and yield very high classification rates when used with a variety... | The foundations of cost-sensitive learning Extracting rules from RBFs is not a trivial task because of nonlinear functions or high input dimensionality. In such cases, some of the hidden units of the RBF network have a tendency to be "shared" across several output classes or even may not contribute ... | Bisection approach for pixel labelling problem This paper formulates pixel labelling as a series of two-category classification. Unlike existing techniques, which assign a determinate label to each pixel, we assign a label set to each pixel and shrink the label set step by step. Determinate labelling is achieved within... | New image descriptors based on color, texture, shape, and wavelets for object and scene image classification. This paper presents new image descriptors based on color, texture, shape, and wavelets for object and scene image classification. First, a new three Dimensional Local Binary Patterns (3D-LBP) descriptor, which ... | Autonomous Detection Of Volcanic Plumes On Outer Planetary Bodies We experimentally evaluated the efficacy of various autonomous supervised classification techniques for detecting transient geophysical phenomena. We demonstrated methods of detecting volcanic plumes on the planetary satellites Io and Enceladus using spa... | 1.0525 | 0.05 | 0.05 | 0.004545 | 0.000561 | 0.000009 | 0.000002 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Accurate visual odometry from a rear parking camera As an increasing number of automatic safety and navigation features are added to modern vehicles, the crucial job of providing real-time localisation is predominantly performed by a single sensor, GPS, despite its well-known failings, particularly in urban environment... | Multi-task Learning of Visual Odometry Estimators. | Semi-parametric models for visual odometry This paper introduces a novel framework for estimating the motion of a robotic car from image information, a scenario widely known as visual odometry. Most current monocular visual odometry algorithms rely on a calibrated camera model and recover relative rotation and translat... | Parallel, real-time monocular visual odometry We present a real-time, accurate, large-scale monocular visual odometry system for real-world autonomous outdoor driving applications. The key contributions of our work are a series of architectural innovations that address the challenge of robust multithreading even for sc... | Fast relocalisation and loop closing in keyframe-based SLAM In this paper we present for the first time a relocalisation method for keyframe-based SLAM that can deal with severe viewpoint change, at frame-rate, in maps containing thousands of keyframes. As this method relies on local features, it permits the interopera... | Vision-Based Mobile Robot Localization And Mapping Using Scale-Invariant Features A key component of a mobile robot system is the A kc, ability to localize itself accurately and build a map of the environment simultaneously. In this paper, a vision-based mobile robot localization and mapping algorithm is described whic... | Visual odometry learning for unmanned aerial vehicles This paper addresses the problem of using visual information to estimate vehicle motion (a.k.a. visual odometry) from a machine learning perspective. The vast majority of current visual odometry algorithms are heavily based on geometry, using a calibrated camera mod... | Rawseeds ground truth collection systems for indoor self-localization and mapping A trustable and accurate ground truth is a key requirement for benchmarking self-localization and mapping algorithms; on the other hand, collection of ground truth is a complex and daunting task, and its validation is a challenging issue.... | Distributed message passing for large scale graphical models In this paper we propose a distributed message-passing algorithm for inference in large scale graphical models. Our method can handle large problems efficiently by distributing and parallelizing the computation and memory requirements. The convergence and opt... | Robust Estimation for an Inverse Problem Arising in Multiview Geometry We propose a new approach to the problem of robust estimation for a class of inverse problems arising in multiview geometry. Inspired by recent advances in the statistical theory of recovering sparse vectors, we define our estimator as a Bayesian ma... | Unscented FastSLAM: A Robust and Efficient Solution to the SLAM Problem The Rao-Blackwellized particle filter (RBPF) and FastSLAM have two important limitations, which are the derivation of the Jacobian matrices and the linear approximations of nonlinear functions. These can make the filter inconsistent. Another challe... | Localization and Matching Using the Planar Trifocal Tensor With Bearing-Only Data This paper addresses the robot and landmark localization problem from bearing-only data in three views, simultaneously to the robust association of this data. The localization algorithm is based on the 1-D trifocal tensor, which relates l... | Maximally stable local description for scale selection Scale and affine-invariant local features have shown excellent performance in image matching, object and texture recognition. This paper optimizes keypoint detection to achieve stable local descriptors, and therefore, an improved image representation. The technique... | Fast Visual Retrieval Using Accelerated Sequence Matching We present an approach to represent, match, and index various types of visual data, with the primary goal of enabling effective and computationally efficient searches. In this approach, an image/video is represented by an ordered list of feature descriptors. Sim... | 1.045934 | 0.035737 | 0.020448 | 0.006584 | 0.003346 | 0.001672 | 0.000756 | 0.000145 | 0.000036 | 0.000016 | 0.000006 | 0.000002 | 0 | 0 |
Contour detection and hierarchical image segmentation. This paper investigates two fundamental problems in computer vision: contour detection and image segmentation. We present state-of-the-art algorithms for both of these tasks. Our contour detector combines multiple local cues into a globalization framework based on ... | A polynomial algorithm for submap isomorphism of general maps Combinatorial maps explicitly encode orientations of edges around vertices, and have been used in many fields. In this paper, we address the problem of searching for patterns in model maps by putting forward the concept of symbol graph. A symbol graph will b... | Multi-Cue Mid-Level Grouping Region proposal methods provide richer object hypotheses than sliding windows with dramatically fewer proposals, yet they still number in the thousands. This large quantity of proposals typically results from a diversification step that propagates bottom-up ambiguity in the form of proposal... | A framework for measuring sharpness in natural images captured by digital cameras based on reference image and local areas. Image quality is a vital criterion that guides the technical development of digital cameras. Traditionally, the image quality of digital cameras has been measured using test-targets and/or subject... | Deep Epitomic Convolutional Neural Networks. Deep convolutional neural networks have recently proven extremely competitive in challenging image recognition tasks. This paper proposes the epitomic convolution as a new building block for deep neural networks. An epitomic convolution layer replaces a pair of consecutive... | Spatial Statistics of Image Features for Performance Comparison When matching images for applications such as mosaicking and homography estimation, the distribution of features across the overlap region affects the accuracy of the result. This paper uses the spatial statistics of these features, measured by Ripley's K-... | Nonparametric Scene Parsing via Label Transfer. While there has been a lot of recent work on object recognition and image understanding, the focus has been on carefully establishing mathematical models for images, scenes and objects. In this paper, we propose a novel, nonparametric approach for object recognition and s... | Semantic Image Segmentation via Deep Parsing Network This paper addresses semantic image segmentation by incorporating rich information into Markov Random Field (MRF), including high-order relations and mixture of label contexts. Unlike previous works that optimized MRFs using iterative algorithm, we solve MRF by propo... | Manhattan Junction Catalogue for Spatial Reasoning of Indoor Scenes Junctions are strong cues for understanding the geometry of a scene. In this paper, we consider the problem of detecting junctions and using them for recovering the spatial layout of an indoor scene. Junction detection has always been challenging due t... | Integrated feature selection and higher-order spatial feature extraction for object categorization In computer vision, the bag-of-visual words image representation has been shown to yield good results. Recent work has shown that modeling the spatial re- lationship between visual words further improves per- formance. Pr... | Structure Is a Visual Class Invariant The problem of learning the class identity of visual objects has received considerable attention recently. With rare exception, all of the work to date assumes low variation in appearance, which limits them to a single depictive style usually photographic. The same object depicted ... | From 3D Point Clouds to Pose-Normalised Depth Maps We consider the problem of generating either pairwise-aligned or pose-normalised depth maps from noisy 3D point clouds in a relatively unrestricted poses. Our system is deployed in a 3D face alignment application and consists of the following four stages: (i) data filt... | Discrete-continuous optimization for large-scale structure from motion Recent work in structure from motion (SfM) has successfully built 3D models from large unstructured collections of images downloaded from the Internet. Most approaches use incremental algorithms that solve progressively larger bundle adjustment prob... | Combined 2D-3D categorization and classification for multimodal perception systems In this article we describe an object perception system for autonomous robots performing everyday manipulation tasks in kitchen environments. The perception system gains its strengths by exploiting that the robots are to perform the same... | 1.003614 | 0.00625 | 0.003785 | 0.003347 | 0.003142 | 0.002171 | 0.001136 | 0.000574 | 0.000311 | 0.000071 | 0.000012 | 0.000003 | 0 | 0 |
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