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25,102 | Cascaded Sparse Spatial Bins for Efficient and Effective Generic Object
Detection | cs.CV | A novel efficient method for extraction of object proposals is introduced.
Its "objectness" function exploits deep spatial pyramid features, a novel
fast-to-compute HoG-based edge statistic and the EdgeBoxes score. The
efficiency is achieved by the use of spatial bins in a novel combination with
sparsity-inducing group... | computer science |
25,103 | Shape Representation and Classification through Pattern Spectrum and
Local Binary Pattern - A Decision Level Fusion Approach | cs.CV | In this paper, we present a decision level fused local Morphological Pattern
Spectrum(PS) and Local Binary Pattern (LBP) approach for an efficient shape
representation and classification. This method makes use of Earth Movers
Distance(EMD) as the measure in feature matching and shape retrieval process.
The proposed app... | computer science |
25,104 | Combining Local Appearance and Holistic View: Dual-Source Deep Neural
Networks for Human Pose Estimation | cs.CV | We propose a new learning-based method for estimating 2D human pose from a
single image, using Dual-Source Deep Convolutional Neural Networks (DS-CNN).
Recently, many methods have been developed to estimate human pose by using pose
priors that are estimated from physiologically inspired graphical models or
learned from... | computer science |
25,105 | Dynamic Body VSLAM with Semantic Constraints | cs.CV | Image based reconstruction of urban environments is a challenging problem
that deals with optimization of large number of variables, and has several
sources of errors like the presence of dynamic objects. Since most large scale
approaches make the assumption of observing static scenes, dynamic objects are
relegated to ... | computer science |
25,106 | Mid-level Elements for Object Detection | cs.CV | Building on the success of recent discriminative mid-level elements, we
propose a surprisingly simple approach for object detection which performs
comparable to the current state-of-the-art approaches on PASCAL VOC comp-3
detection challenge (no external data). Through extensive experiments and
ablation analysis, we sh... | computer science |
25,107 | Convolutional Channel Features | cs.CV | Deep learning methods are powerful tools but often suffer from expensive
computation and limited flexibility. An alternative is to combine light-weight
models with deep representations. As successful cases exist in several visual
problems, a unified framework is absent. In this paper, we revisit two widely
used approac... | computer science |
25,108 | Embedded Platforms for Computer Vision-based Advanced Driver Assistance
Systems: a Survey | cs.CV | Computer Vision, either alone or combined with other technologies such as
radar or Lidar, is one of the key technologies used in Advanced Driver
Assistance Systems (ADAS). Its role understanding and analysing the driving
scene is of great importance as it can be noted by the number of ADAS
applications that use this te... | computer science |
25,109 | Identifying Reliable Annotations for Large Scale Image Segmentation | cs.CV | Challenging computer vision tasks, in particular semantic image segmentation,
require large training sets of annotated images. While obtaining the actual
images is often unproblematic, creating the necessary annotation is a tedious
and costly process. Therefore, one often has to work with unreliable annotation
sources,... | computer science |
25,110 | Compact CNN for Indexing Egocentric Videos | cs.CV | While egocentric video is becoming increasingly popular, browsing it is very
difficult. In this paper we present a compact 3D Convolutional Neural Network
(CNN) architecture for long-term activity recognition in egocentric videos.
Recognizing long-term activities enables us to temporally segment (index) long
and unstru... | computer science |
25,111 | Speeding Up Neural Networks for Large Scale Classification using WTA
Hashing | cs.CV | In this paper we propose to use the Winner Takes All hashing technique to
speed up forward propagation and backward propagation in fully connected layers
in convolutional neural networks. The proposed technique reduces significantly
the computational complexity, which in turn, allows us to train layers with a
large num... | computer science |
25,112 | A Robust Lane Detection and Departure Warning System | cs.CV | In this work, we have developed a robust lane detection and departure warning
technique. Our system is based on single camera sensor. For lane detection a
modified Inverse Perspective Mapping using only a few extrinsic camera
parameters and illuminant Invariant techniques is used. Lane markings are
represented using a ... | computer science |
25,113 | Intelligent Health Recommendation System for Computer Users | cs.CV | The time people spend in front of computers has been increasing steadily due
to the role computers play in modern society. Individuals who sit in front of
computers for an extended period of time, specifically with improper postures
may incur various health issues. In this work, individuals' behaviors in front
of compu... | computer science |
25,114 | Bilinear CNNs for Fine-grained Visual Recognition | cs.CV | We present a simple and effective architecture for fine-grained visual
recognition called Bilinear Convolutional Neural Networks (B-CNNs). These
networks represent an image as a pooled outer product of features derived from
two CNNs and capture localized feature interactions in a translationally
invariant manner. B-CNN... | computer science |
25,115 | Comparative study of image registration techniques for bladder
video-endoscopy | cs.CV | Bladder cancer is widely spread in the world. Many adequate diagnosis
techniques exist. Video-endoscopy remains the standard clinical procedure for
visual exploration of the bladder internal surface. However, video-endoscopy
presents the limit that the imaged area for each image is about nearly 1cm2.
And, lesions are, ... | computer science |
25,116 | A Flexible Tensor Block Coordinate Ascent Scheme for Hypergraph Matching | cs.CV | The estimation of correspondences between two images resp. point sets is a
core problem in computer vision. One way to formulate the problem is graph
matching leading to the quadratic assignment problem which is NP-hard. Several
so called second order methods have been proposed to solve this problem. In
recent years hy... | computer science |
25,117 | Robust hyperspectral image classification with rejection fields | cs.CV | In this paper we present a novel method for robust hyperspectral image
classification using context and rejection. Hyperspectral image classification
is generally an ill-posed image problem where pixels may belong to unknown
classes, and obtaining representative and complete training sets is costly.
Furthermore, the ne... | computer science |
25,118 | Patch-based Convolutional Neural Network for Whole Slide Tissue Image
Classification | cs.CV | Convolutional Neural Networks (CNN) are state-of-the-art models for many
image classification tasks. However, to recognize cancer subtypes
automatically, training a CNN on gigapixel resolution Whole Slide Tissue Images
(WSI) is currently computationally impossible. The differentiation of cancer
subtypes is based on cel... | computer science |
25,119 | Exploring Integral Image Word Length Reduction Techniques for SURF
Detector | cs.CV | Speeded Up Robust Features (SURF) is a state of the art computer vision
algorithm that relies on integral image representation for performing fast
detection and description of image features that are scale and rotation
invariant. Integral image representation, however, has major draw back of large
binary word length th... | computer science |
25,120 | Hardware based Scale- and Rotation-Invariant Feature Extraction: A
Retrospective Analysis and Future Directions | cs.CV | Computer Vision techniques represent a class of algorithms that are highly
computation and data intensive in nature. Generally, performance of these
algorithms in terms of execution speed on desktop computers is far from
real-time. Since real-time performance is desirable in many applications,
special-purpose hardware ... | computer science |
25,121 | Anticipating Visual Representations from Unlabeled Video | cs.CV | Anticipating actions and objects before they start or appear is a difficult
problem in computer vision with several real-world applications. This task is
challenging partly because it requires leveraging extensive knowledge of the
world that is difficult to write down. We believe that a promising resource for
efficient... | computer science |
25,122 | Fast R-CNN | cs.CV | This paper proposes a Fast Region-based Convolutional Network method (Fast
R-CNN) for object detection. Fast R-CNN builds on previous work to efficiently
classify object proposals using deep convolutional networks. Compared to
previous work, Fast R-CNN employs several innovations to improve training and
testing speed w... | computer science |
25,123 | Predicting People's 3D Poses from Short Sequences | cs.CV | We propose an efficient approach to exploiting motion information from
consecutive frames of a video sequence to recover the 3D pose of people.
Instead of computing candidate poses in individual frames and then linking
them, as is often done, we regress directly from a spatio-temporal block of
frames to a 3D pose in th... | computer science |
25,124 | Neural Activation Constellations: Unsupervised Part Model Discovery with
Convolutional Networks | cs.CV | Part models of object categories are essential for challenging recognition
tasks, where differences in categories are subtle and only reflected in
appearances of small parts of the object. We present an approach that is able
to learn part models in a completely unsupervised manner, without part
annotations and even wit... | computer science |
25,125 | Efficient Image-Space Extraction and Representation of 3D Surface
Topography | cs.CV | Surface topography refers to the geometric micro-structure of a surface and
defines its tactile characteristics (typically in the sub-millimeter range).
High-resolution 3D scanning techniques developed recently enable the 3D
reconstruction of surfaces including their surface topography. In his paper, we
present an effi... | computer science |
25,126 | PerforatedCNNs: Acceleration through Elimination of Redundant
Convolutions | cs.CV | We propose a novel approach to reduce the computational cost of evaluation of
convolutional neural networks, a factor that has hindered their deployment in
low-power devices such as mobile phones. Inspired by the loop perforation
technique from source code optimization, we speed up the bottleneck
convolutional layers b... | computer science |
25,127 | Bag-of-Genres for Video Genre Retrieval | cs.CV | This paper presents a higher level representation for videos aiming at video
genre retrieval. In video genre retrieval, there is a challenge that videos may
comprise multiple categories, for instance, news videos may be composed of
sports, documentary, and action. Therefore, it is interesting to encode the
distribution... | computer science |
25,128 | A Review of Feature and Data Fusion with Medical Images | cs.CV | The fusion techniques that utilize multiple feature sets to form new features
that are often more robust and contain useful information for future processing
are referred to as feature fusion. The term data fusion is applied to the class
of techniques used for combining decisions obtained from multiple feature sets
to ... | computer science |
25,129 | Using curvature to distinguish between surface reflections and vessel
contents in computer vision based recognition of materials in transparent
vessels | cs.CV | The recognition of materials and objects inside transparent containers using
computer vision has a wide range of applications, ranging from industrial
bottles filling to the automation of chemistry laboratory. One of the main
challenges in such recognition is the ability to distinguish between image
features resulting ... | computer science |
25,130 | RBIR using Interest Regions and Binary Signatures | cs.CV | In this paper, we introduce an approach to overcome the low accuracy of the
Content-Based Image Retrieval (CBIR) (when using the global features). To
increase the accuracy, we use Harris-Laplace detector to identify the interest
regions of image. Then, we build the Region-Based Image Retrieval (RBIR). For
the efficient... | computer science |
25,131 | Hierarchical structure-and-motion recovery from uncalibrated images | cs.CV | This paper addresses the structure-and-motion problem, that requires to find
camera motion and 3D struc- ture from point matches. A new pipeline, dubbed
Samantha, is presented, that departs from the prevailing sequential paradigm
and embraces instead a hierarchical approach. This method has several
advantages, like a p... | computer science |
25,132 | An Efficient Algorithm for Video Super-Resolution Based On a Sequential
Model | cs.CV | In this work, we propose a novel procedure for video super-resolution, that
is the recovery of a sequence of high-resolution images from its low-resolution
counterpart. Our approach is based on a "sequential" model (i.e., each
high-resolution frame is supposed to be a displaced version of the preceding
one) and conside... | computer science |
25,133 | Robust Face Recognition with Structural Binary Gradient Patterns | cs.CV | This paper presents a computationally efficient yet powerful binary framework
for robust facial representation based on image gradients. It is termed as
structural binary gradient patterns (SBGP). To discover underlying local
structures in the gradient domain, we compute image gradients from multiple
directions and sim... | computer science |
25,134 | What Makes Kevin Spacey Look Like Kevin Spacey | cs.CV | We reconstruct a controllable model of a person from a large photo collection
that captures his or her {\em persona}, i.e., physical appearance and behavior.
The ability to operate on unstructured photo collections enables modeling a
huge number of people, including celebrities and other well photographed people
withou... | computer science |
25,135 | Image Retrieval Based on Binary Signature ang S-kGraph | cs.CV | In this paper, we introduce an optimum approach for querying similar images
on large digital-image databases. Our work is based on RBIR (region-based image
retrieval) method which uses multiple regions as the key to retrieval images.
This method significantly improves the accuracy of queries. However, this also
increas... | computer science |
25,136 | Classify Images with Conceptor Network | cs.CV | This article demonstrates a new conceptor network based classifier in
classifying images. Mathematical descriptions and analysis are presented.
Various tests are experimented using three benchmark datasets: MNIST, CIFAR-10
and CIFAR-100. The experiments displayed that conceptor network can offer
superior results and fl... | computer science |
25,137 | Facial Expressions Tracking and Recognition: Database Protocols for
Systems Validation and Evaluation | cs.CV | Each human face is unique. It has its own shape, topology, and distinguishing
features. As such, developing and testing facial tracking systems are
challenging tasks. The existing face recognition and tracking algorithms in
Computer Vision mainly specify concrete situations according to particular
goals and application... | computer science |
25,138 | Bilinear Random Projections for Locality-Sensitive Binary Codes | cs.CV | Locality-sensitive hashing (LSH) is a popular data-independent indexing
method for approximate similarity search, where random projections followed by
quantization hash the points from the database so as to ensure that the
probability of collision is much higher for objects that are close to each
other than for those t... | computer science |
25,139 | Hyperspectral Image Classification and Clutter Detection via Multiple
Structural Embeddings and Dimension Reductions | cs.CV | We present a new and effective approach for Hyperspectral Image (HSI)
classification and clutter detection, overcoming a few long-standing challenges
presented by HSI data characteristics. Residing in a high-dimensional spectral
attribute space, HSI data samples are known to be strongly correlated in their
spectral sig... | computer science |
25,140 | Unsupervised domain adaption dictionary learning for visual recognition | cs.CV | Over the last years, dictionary learning method has been extensively applied
to deal with various computer vision recognition applications, and produced
state-of-the-art results. However, when the data instances of a target domain
have a different distribution than that of a source domain, the dictionary
learning metho... | computer science |
25,141 | What value do explicit high level concepts have in vision to language
problems? | cs.CV | Much of the recent progress in Vision-to-Language (V2L) problems has been
achieved through a combination of Convolutional Neural Networks (CNNs) and
Recurrent Neural Networks (RNNs). This approach does not explicitly represent
high-level semantic concepts, but rather seeks to progress directly from image
features to te... | computer science |
25,142 | Understanding deep features with computer-generated imagery | cs.CV | We introduce an approach for analyzing the variation of features generated by
convolutional neural networks (CNNs) with respect to scene factors that occur
in natural images. Such factors may include object style, 3D viewpoint, color,
and scene lighting configuration. Our approach analyzes CNN feature responses
corresp... | computer science |
25,143 | Color Image Retrieval Using Fuzzy Measure Hamming and S-Tree | cs.CV | This chapter approaches the image retrieval system on the base of the colors
of image. It creates fuzzy signature to describe the color of image on color
space HSV and builds fuzzy Hamming distance (FHD) to evaluate the similarity
between the images. In order to reduce the storage space and speed up the
search of simil... | computer science |
25,144 | One-to-many face recognition with bilinear CNNs | cs.CV | The recent explosive growth in convolutional neural network (CNN) research
has produced a variety of new architectures for deep learning. One intriguing
new architecture is the bilinear CNN (B-CNN), which has shown dramatic
performance gains on certain fine-grained recognition problems [15]. We apply
this new CNN to th... | computer science |
25,145 | Recognition of Changes in SAR Images Based on Gauss-Log Ratio and MRFFCM | cs.CV | A modified version of MRFFCM (Markov Random Field Fuzzy C means) based SAR
(Synthetic aperture Radar) image change detection method is proposed in this
paper. It involves three steps: Difference Image (DI) generation by using
Gauss-log ratio operator, speckle noise reduction by SRAD (Speckle Reducing
Anisotropic Diffus... | computer science |
25,146 | Comparing the Performance of L*A*B* and HSV Color Spaces with Respect to
Color Image Segmentation | cs.CV | Color image segmentation is a very emerging topic for image processing
research. Since it has the ability to present the result in a way that is much
more close to the human yes perceive, so todays more research is going on this
area. Choosing a proper color space is a very important issue for color image
segmentation ... | computer science |
25,147 | Faster R-CNN: Towards Real-Time Object Detection with Region Proposal
Networks | cs.CV | State-of-the-art object detection networks depend on region proposal
algorithms to hypothesize object locations. Advances like SPPnet and Fast R-CNN
have reduced the running time of these detection networks, exposing region
proposal computation as a bottleneck. In this work, we introduce a Region
Proposal Network (RPN)... | computer science |
25,148 | Multilayer Structured NMF for Spectral Unmixing of Hyperspectral Images | cs.CV | One of the challenges in hyperspectral data analysis is the presence of mixed
pixels. Mixed pixels are the result of low spatial resolution of hyperspectral
sensors. Spectral unmixing methods decompose a mixed pixel into a set of
endmembers and abundance fractions. Due to nonnegativity constraint on
abundance fraction ... | computer science |
25,149 | A Novel Approach Towards Clustering Based Image Segmentation | cs.CV | In computer vision, image segmentation is always selected as a major research
topic by researchers. Due to its vital rule in image processing, there always
arises the need of a better image segmentation method. Clustering is an
unsupervised study with its application in almost every field of science and
engineering. Ma... | computer science |
25,150 | Learning to track for spatio-temporal action localization | cs.CV | We propose an effective approach for spatio-temporal action localization in
realistic videos. The approach first detects proposals at the frame-level and
scores them with a combination of static and motion CNN features. It then
tracks high-scoring proposals throughout the video using a
tracking-by-detection approach. O... | computer science |
25,151 | Facial Expressions recognition Based on Principal Component Analysis
(PCA) | cs.CV | The facial expression recognition is an ocular task that can be performed
without human discomfort, is really a speedily growing on the computer research
field. There are many applications and programs uses facial expression to
evaluate human character, judgment, feelings, and viewpoint. The process of
recognizing faci... | computer science |
25,152 | Spatial Transformer Networks | cs.CV | Convolutional Neural Networks define an exceptionally powerful class of
models, but are still limited by the lack of ability to be spatially invariant
to the input data in a computationally and parameter efficient manner. In this
work we introduce a new learnable module, the Spatial Transformer, which
explicitly allows... | computer science |
25,153 | Sentence Directed Video Object Codetection | cs.CV | We tackle the problem of video object codetection by leveraging the weak
semantic constraint implied by sentences that describe the video content.
Unlike most existing work that focuses on codetecting large objects which are
usually salient both in size and appearance, we can codetect objects that are
small or medium s... | computer science |
25,154 | What's the Point: Semantic Segmentation with Point Supervision | cs.CV | The semantic image segmentation task presents a trade-off between test time
accuracy and training-time annotation cost. Detailed per-pixel annotations
enable training accurate models but are very time-consuming to obtain,
image-level class labels are an order of magnitude cheaper but result in less
accurate models. We ... | computer science |
25,155 | Color Constancy by Learning to Predict Chromaticity from Luminance | cs.CV | Color constancy is the recovery of true surface color from observed color,
and requires estimating the chromaticity of scene illumination to correct for
the bias it induces. In this paper, we show that the per-pixel color statistics
of natural scenes---without any spatial or semantic context---can by themselves
be a po... | computer science |
25,156 | Capturing Hands in Action using Discriminative Salient Points and
Physics Simulation | cs.CV | Hand motion capture is a popular research field, recently gaining more
attention due to the ubiquity of RGB-D sensors. However, even most recent
approaches focus on the case of a single isolated hand. In this work, we focus
on hands that interact with other hands or objects and present a framework that
successfully cap... | computer science |
25,157 | First-Take-All: Temporal Order-Preserving Hashing for 3D Action Videos | cs.CV | With the prevalence of the commodity depth cameras, the new paradigm of user
interfaces based on 3D motion capturing and recognition have dramatically
changed the way of interactions between human and computers. Human action
recognition, as one of the key components in these devices, plays an important
role to guarante... | computer science |
25,158 | Describing Common Human Visual Actions in Images | cs.CV | Which common human actions and interactions are recognizable in monocular
still images? Which involve objects and/or other people? How many is a person
performing at a time? We address these questions by exploring the actions and
interactions that are detectable in the images of the MS COCO dataset. We make
two main co... | computer science |
25,159 | Boosting Optical Character Recognition: A Super-Resolution Approach | cs.CV | Text image super-resolution is a challenging yet open research problem in the
computer vision community. In particular, low-resolution images hamper the
performance of typical optical character recognition (OCR) systems. In this
article, we summarize our entry to the ICDAR2015 Competition on Text Image
Super-Resolution... | computer science |
25,160 | Well-posedness of a nonlinear integro-differential problem and its
rearranged formulation | cs.CV | We study the existence and uniqueness of solutions of a nonlinear
integro-differential problem which we reformulate introducing the notion of the
decreasing rearrangement of the solution. A dimensional reduction of the
problem is obtained and a detailed analysis of the properties of the solutions
of the model is provid... | computer science |
25,161 | Randomized Structural Sparsity based Support Identification with
Applications to Locating Activated or Discriminative Brain Areas: A
Multi-center Reproducibility Study | cs.CV | In this paper, we focus on how to locate the relevant or discriminative brain
regions related with external stimulus or certain mental decease, which is also
called support identification, based on the neuroimaging data. The main
difficulty lies in the extremely high dimensional voxel space and relatively
few training ... | computer science |
25,162 | EventNet: A Large Scale Structured Concept Library for Complex Event
Detection in Video | cs.CV | Event-specific concepts are the semantic concepts designed for the events of
interest, which can be used as a mid-level representation of complex events in
videos. Existing methods only focus on defining event-specific concepts for a
small number of predefined events, but cannot handle novel unseen events. This
motivat... | computer science |
25,163 | Wavelets and continuous wavelet transform for autostereoscopic multiview
images | cs.CV | Recently, the reference functions for the synthesis and analysis of the
autostereoscopic multiview and integral images in three-dimensional displays we
introduced. In the current paper, we propose the wavelets to analyze such
images. The wavelets are built on the reference functions as on the scaling
functions of the w... | computer science |
25,164 | Reflection Invariance: an important consideration of image orientation | cs.CV | In this position paper, we consider the state of computer vision research
with respect to invariance to the horizontal orientation of an image -- what we
term reflection invariance. We describe why we consider reflection invariance
to be an important property and provide evidence where the absence of this
invariance pr... | computer science |
25,165 | Fast ConvNets Using Group-wise Brain Damage | cs.CV | We revisit the idea of brain damage, i.e. the pruning of the coefficients of
a neural network, and suggest how brain damage can be modified and used to
speedup convolutional layers. The approach uses the fact that many efficient
implementations reduce generalized convolutions to matrix multiplications. The
suggested br... | computer science |
25,166 | Circulant temporal encoding for video retrieval and temporal alignment | cs.CV | We address the problem of specific video event retrieval. Given a query video
of a specific event, e.g., a concert of Madonna, the goal is to retrieve other
videos of the same event that temporally overlap with the query. Our approach
encodes the frame descriptors of a video to jointly represent their appearance
and te... | computer science |
25,167 | You Only Look Once: Unified, Real-Time Object Detection | cs.CV | We present YOLO, a new approach to object detection. Prior work on object
detection repurposes classifiers to perform detection. Instead, we frame object
detection as a regression problem to spatially separated bounding boxes and
associated class probabilities. A single neural network predicts bounding boxes
and class ... | computer science |
25,168 | Fast Geometric Fit Algorithm for Sphere Using Exact Solution | cs.CV | Sphere fitting is a common problem in almost all science and engineering
disciplines. Most of methods available are iterative in behavior. This involves
fitting of the parameters in a least square sense or in a geometric sense. Here
we extend the methods of Thomas Chan and Landau who fitted the 2D data using
circle. Th... | computer science |
25,169 | Flowing ConvNets for Human Pose Estimation in Videos | cs.CV | The objective of this work is human pose estimation in videos, where multiple
frames are available. We investigate a ConvNet architecture that is able to
benefit from temporal context by combining information across the multiple
frames using optical flow.
To this end we propose a network architecture with the followi... | computer science |
25,170 | Compact Shape Trees: A Contribution to the Forest of Shape
Correspondences and Matching Methods | cs.CV | We propose a novel technique, termed compact shape trees, for computing
correspondences of single-boundary 2-D shapes in O(n2) time. Together with zero
or more features defined at each of n sample points on the shape's boundary,
the compact shape tree of a shape comprises the O(n) collection of vectors
emanating from a... | computer science |
25,171 | Learning to Linearize Under Uncertainty | cs.CV | Training deep feature hierarchies to solve supervised learning tasks has
achieved state of the art performance on many problems in computer vision.
However, a principled way in which to train such hierarchies in the
unsupervised setting has remained elusive. In this work we suggest a new
architecture and loss for train... | computer science |
25,172 | License Plate Recognition System Based on Color Coding Of License Plates | cs.CV | License Plate Recognition Systems are used to determine the license plate
number of a vehicle. The current system mainly uses Optical Character
Recognition to recognize the number plate. There are several problems to this
system. Some of them include interchanging of several letters or numbers
(letter O with digit 0), ... | computer science |
25,173 | ICDAR 2015 Text Reading in the Wild Competition | cs.CV | Recently, text detection and recognition in natural scenes are becoming
increasing popular in the computer vision community as well as the document
analysis community. However, majority of the existing ideas, algorithms and
systems are specifically designed for English. This technical report presents
the final results ... | computer science |
25,174 | Wide baseline stereo matching with convex bounded-distortion constraints | cs.CV | Finding correspondences in wide baseline setups is a challenging problem.
Existing approaches have focused largely on developing better feature
descriptors for correspondence and on accurate recovery of epipolar line
constraints. This paper focuses on the challenging problem of finding
correspondences once approximate ... | computer science |
25,175 | LSUN: Construction of a Large-scale Image Dataset using Deep Learning
with Humans in the Loop | cs.CV | While there has been remarkable progress in the performance of visual
recognition algorithms, the state-of-the-art models tend to be exceptionally
data-hungry. Large labeled training datasets, expensive and tedious to produce,
are required to optimize millions of parameters in deep network models. Lagging
behind the gr... | computer science |
25,176 | Image Tag Completion and Refinement by Subspace Clustering and Matrix
Completion | cs.CV | Tag-based image retrieval (TBIR) has drawn much attention in recent years due
to the explosive amount of digital images and crowdsourcing tags. However, the
TBIR applications still suffer from the deficient and inaccurate tags provided
by users. Inspired by the subspace clustering methods, we formulate the tag
completi... | computer science |
25,177 | BoWFire: Detection of Fire in Still Images by Integrating Pixel Color
and Texture Analysis | cs.CV | Emergency events involving fire are potentially harmful, demanding a fast and
precise decision making. The use of crowdsourcing image and videos on crisis
management systems can aid in these situations by providing more information
than verbal/textual descriptions. Due to the usual high volume of data,
automatic soluti... | computer science |
25,178 | P-CNN: Pose-based CNN Features for Action Recognition | cs.CV | This work targets human action recognition in video. While recent methods
typically represent actions by statistics of local video features, here we
argue for the importance of a representation derived from human pose. To this
end we propose a new Pose-based Convolutional Neural Network descriptor (P-CNN)
for action re... | computer science |
25,179 | Pose-Invariant 3D Face Alignment | cs.CV | Face alignment aims to estimate the locations of a set of landmarks for a
given image. This problem has received much attention as evidenced by the
recent advancement in both the methodology and performance. However, most of
the existing works neither explicitly handle face images with arbitrary poses,
nor perform larg... | computer science |
25,180 | Techniques for effective and efficient fire detection from social media
images | cs.CV | Social media could provide valuable information to support decision making in
crisis management, such as in accidents, explosions and fires. However, much of
the data from social media are images, which are uploaded in a rate that makes
it impossible for human beings to analyze them. Despite the many works on image
ana... | computer science |
25,181 | A Novel Hybrid Approach for Cephalometric Landmark Detection | cs.CV | Cephalometric analysis has an important role in dentistry and especially in
orthodontics as a treatment planning tool to gauge the size and special
relationships of the teeth, jaws and cranium. The first step of using such
analyses is localizing some important landmarks known as cephalometric
landmarks on craniofacial ... | computer science |
25,182 | Technical Report: Image Captioning with Semantically Similar Images | cs.CV | This report presents our submission to the MS COCO Captioning Challenge 2015.
The method uses Convolutional Neural Network activations as an embedding to
find semantically similar images. From these images, the most typical caption
is selected based on unigram frequencies. Although the method received low
scores with a... | computer science |
25,183 | Towards Benchmarking Scene Background Initialization | cs.CV | Given a set of images of a scene taken at different times, the availability
of an initial background model that describes the scene without foreground
objects is the prerequisite for a wide range of applications, ranging from
video surveillance to computational photography. Even though several methods
have been propose... | computer science |
25,184 | Deep Structured Models For Group Activity Recognition | cs.CV | This paper presents a deep neural-network-based hierarchical graphical model
for individual and group activity recognition in surveillance scenes. Deep
networks are used to recognize the actions of individual people in a scene.
Next, a neural-network-based hierarchical graphical model refines the predicted
labels for e... | computer science |
25,185 | Convolutional LSTM Network: A Machine Learning Approach for
Precipitation Nowcasting | cs.CV | The goal of precipitation nowcasting is to predict the future rainfall
intensity in a local region over a relatively short period of time. Very few
previous studies have examined this crucial and challenging weather forecasting
problem from the machine learning perspective. In this paper, we formulate
precipitation now... | computer science |
25,186 | Combinatorial Energy Learning for Image Segmentation | cs.CV | We introduce a new machine learning approach for image segmentation that uses
a neural network to model the conditional energy of a segmentation given an
image. Our approach, combinatorial energy learning for image segmentation
(CELIS) places a particular emphasis on modeling the inherent combinatorial
nature of dense ... | computer science |
25,187 | Resolving Scale Ambiguity Via XSlit Aspect Ratio Analysis | cs.CV | In perspective cameras, images of a frontal-parallel 3D object preserve its
aspect ratio invariant to its depth. Such an invariance is useful in
photography but is unique to perspective projection. In this paper, we show
that alternative non-perspective cameras such as the crossed-slit or XSlit
cameras exhibit a differ... | computer science |
25,188 | Deep Secure Encoding: An Application to Face Recognition | cs.CV | In this paper we present Deep Secure Encoding: a framework for secure
classification using deep neural networks, and apply it to the task of
biometric template protection for faces. Using deep convolutional neural
networks (CNNs), we learn a robust mapping of face classes to high entropy
secure codes. These secure code... | computer science |
25,189 | Reading Scene Text in Deep Convolutional Sequences | cs.CV | We develop a Deep-Text Recurrent Network (DTRN) that regards scene text
reading as a sequence labelling problem. We leverage recent advances of deep
convolutional neural networks to generate an ordered high-level sequence from a
whole word image, avoiding the difficult character segmentation problem. Then a
deep recurr... | computer science |
25,190 | A Survey of Multithreading Image Analysis | cs.CV | Digital image analysis has made a big advance in many areas of enterprise
applications including medicine, industry, and entertainment by assisting the
extraction of semantic information from digital images. However, its large
computational complexity has been a trouble to most real-time developments.
While image analy... | computer science |
25,191 | Circle-based Eye Center Localization (CECL) | cs.CV | We propose an improved eye center localization method based on the Hough
transform, called Circle-based Eye Center Localization (CECL) that is simple,
robust, and achieves accuracy on a par with typically more complex
state-of-the-art methods. The CECL method relies on color and shape cues that
distinguish the iris fro... | computer science |
25,192 | ParseNet: Looking Wider to See Better | cs.CV | We present a technique for adding global context to deep convolutional
networks for semantic segmentation. The approach is simple, using the average
feature for a layer to augment the features at each location. In addition, we
study several idiosyncrasies of training, significantly increasing the
performance of baselin... | computer science |
25,193 | Flow Segmentation in Dense Crowds | cs.CV | A framework is proposed in this paper that is used to segment flow of dense
crowds. The flow field that is generated by the movement in the crowd is
treated just like an aperiodic dynamic system. On this flow field a grid of
particles is put over for particle advection by the use of a numerical
integration scheme. Then... | computer science |
25,194 | Thin Structure Estimation with Curvature Regularization | cs.CV | Many applications in vision require estimation of thin structures such as
boundary edges, surfaces, roads, blood vessels, neurons, etc. Unlike most
previous approaches, we simultaneously detect and delineate thin structures
with sub-pixel localization and real-valued orientation estimation. This is an
ill-posed problem... | computer science |
25,195 | Leveraging the Power of Gabor Phase for Face Identification: A Block
Matching Approach | cs.CV | Different from face verification, face identification is much more demanding.
To reach comparable performance, an identifier needs to be roughly N times
better than a verifier. To expect a breakthrough in face identification, we
need a fresh look at the fundamental building blocks of face recognition. In
this paper we ... | computer science |
25,196 | Multi-path Convolutional Neural Networks for Complex Image
Classification | cs.CV | Convolutional Neural Networks demonstrate high performance on ImageNet
Large-Scale Visual Recognition Challenges contest. Nevertheless, the published
results only show the overall performance for all image classes. There is no
further analysis why certain images get worse results and how they could be
improved. In this... | computer science |
25,197 | Slow and steady feature analysis: higher order temporal coherence in
video | cs.CV | How can unlabeled video augment visual learning? Existing methods perform
"slow" feature analysis, encouraging the representations of temporally close
frames to exhibit only small differences. While this standard approach captures
the fact that high-level visual signals change slowly over time, it fails to
capture *how... | computer science |
25,198 | Automatic Layer Separation using Light Field Imaging | cs.CV | We propose a novel approach that jointly removes reflection or translucent
layer from a scene and estimates scene depth. The input data are captured via
light field imaging. The problem is couched as minimizing the rank of the
transmitted scene layer via Robust Principle Component Analysis (RPCA). We also
impose regula... | computer science |
25,199 | Layered Interpretation of Street View Images | cs.CV | We propose a layered street view model to encode both depth and semantic
information on street view images for autonomous driving. Recently, stixels,
stix-mantics, and tiered scene labeling methods have been proposed to model
street view images. We propose a 4-layer street view model, a compact
representation over the ... | computer science |
25,200 | Evaluation of Denoising Techniques for EOG signals based on SNR
Estimation | cs.CV | This paper evaluates four algorithms for denoising raw Electrooculography
(EOG) data based on the Signal to Noise Ratio (SNR). The SNR is computed using
the eigenvalue method. The filtering algorithms are a) Finite Impulse Response
(FIR) bandpass filters, b) Stationary Wavelet Transform, c) Empirical Mode
Decomposition... | computer science |
25,201 | End-to-end people detection in crowded scenes | cs.CV | Current people detectors operate either by scanning an image in a sliding
window fashion or by classifying a discrete set of proposals. We propose a
model that is based on decoding an image into a set of people detections. Our
system takes an image as input and directly outputs a set of distinct detection
hypotheses. B... | computer science |
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