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Numerous approaches in image processing and computer vision are making use of super-pixels as a pre-processing step. Among the different methods producing such over-segmentation of an image, the graph-based approach of Felzenszwalb and Huttenlocher is broadly employed. One of its interesting properties is that the regi... | Causal graph-based video segmentation | 3,700 |
Some types of medical and topographic imaging device produce images in which the pixel values are "phase-wrapped", i.e. measured modulus a known scalar. Phase unwrapping can be viewed as the problem of inferring the number of shifts between each and every pair of neighboring pixels, subject to an a priori preference fo... | A Factorized Variational Technique for Phase Unwrapping in Markov Random
Fields | 3,701 |
We present the clustering learning technique applied to multi-layer feedforward deep neural networks. We show that this unsupervised learning technique can compute network filters with only a few minutes and a much reduced set of parameters. The goal of this paper is to promote the technique for general-purpose robotic... | Clustering Learning for Robotic Vision | 3,702 |
Both pixel-based scale saliency (PSS) and basis project methods focus on multiscale analysis of data content and structure. Their theoretical relations and practical combination are previously discussed. However, no models have ever been proposed for calculating scale saliency on basis-projected descriptors since then.... | Wavelet-based Scale Saliency | 3,703 |
This paper presents a basic enhancement to the DeSTIN deep learning architecture by replacing the explicitly calculated transition tables that are used to capture temporal features with a simpler, more scalable mechanism. This mechanism uses feedback of state information to cluster over a space comprised of both the sp... | Recurrent Online Clustering as a Spatio-Temporal Feature Extractor in
DeSTIN | 3,704 |
We describe a method for cell-division detection based on a geometric-driven descriptor that can be represented as a 5-layers processing network, based mainly on wavelet filtering and a test for mirror symmetry between pairs of pixels. After the centroids of the descriptors are computed for a sequence of frames, the tw... | A Geometric Descriptor for Cell-Division Detection | 3,705 |
This paper describes serial and parallel compositional models of multiple objects with part sharing. Objects are built by part-subpart compositions and expressed in terms of a hierarchical dictionary of object parts. These parts are represented on lattices of decreasing sizes which yield an executive summary descriptio... | Complexity of Representation and Inference in Compositional Models with
Part Sharing | 3,706 |
This work addresses multi-class segmentation of indoor scenes with RGB-D inputs. While this area of research has gained much attention recently, most works still rely on hand-crafted features. In contrast, we apply a multiscale convolutional network to learn features directly from the images and the depth information. ... | Indoor Semantic Segmentation using depth information | 3,707 |
Hyper-parameter selection remains a daunting task when building a pattern recognition architecture which performs well, particularly in recently constructed visual pipeline models for feature extraction. We re-formulate pooling in an existing pipeline as a function of adjustable pooling map weight parameters and propos... | Gradient Driven Learning for Pooling in Visual Pipeline Feature
Extraction Models | 3,708 |
The bottom-up saliency, an early stage of humans' visual attention, can be considered as a binary classification problem between center and surround classes. Discriminant power of features for the classification is measured as mutual information between features and two classes distribution. The estimated discrepancy o... | Multiscale Discriminant Saliency for Visual Attention | 3,709 |
In this paper we address the problem of offline Arabic handwriting word recognition. Off-line recognition of handwritten words is a difficult task due to the high variability and uncertainty of human writing. The majority of the recent systems are constrained by the size of the lexicon to deal with and the number of wr... | Multiple models of Bayesian networks applied to offline recognition of
Arabic handwritten city names | 3,710 |
The need for an automatic lip-reading system is ever increasing. Infact, today, extraction and reliable analysis of facial movements make up an important part in many multimedia systems such as videoconference, low communication systems, lip-reading systems. In addition, visual information is imperative among people wi... | Lip Localization and Viseme Classification for Visual Speech Recognition | 3,711 |
Segmentation of an object from a video is a challenging task in multimedia applications. Depending on the application, automatic or interactive methods are desired; however, regardless of the application type, efficient computation of video object segmentation is crucial for time-critical applications; specifically, mo... | Efficient MRF Energy Propagation for Video Segmentation via Bilateral
Filters | 3,712 |
Localization of chess-board vertices is a common task in computer vision, underpinning many applications, but relatively little work focusses on designing a specific feature detector that is fast, accurate and robust. In this paper the `Chess-board Extraction by Subtraction and Summation' (ChESS) feature detector, desi... | ChESS - Quick and Robust Detection of Chess-board Features | 3,713 |
We examine in this paper the problem of image registration from the new perspective where images are given by sparse approximations in parametric dictionaries of geometric functions. We propose a registration algorithm that looks for an estimate of the global transformation between sparse images by examining the set of... | Image registration with sparse approximations in parametric dictionaries | 3,714 |
Face recognition (FR) is an important task in pattern recognition and computer vision. Sparse representation (SR) has been demonstrated to be a powerful framework for FR. In general, an SR algorithm treats each face in a training dataset as a basis function, and tries to find a sparse representation of a test face unde... | Robust Face Recognition via Block Sparse Bayesian Learning | 3,715 |
The bottom-up saliency, an early stage of humans' visual attention, can be considered as a binary classification problem between centre and surround classes. Discriminant power of features for the classification is measured as mutual information between distributions of image features and corresponding classes . As the... | Multi-scale Discriminant Saliency with Wavelet-based Hidden Markov Tree
Modelling | 3,716 |
This paper formulates bottom-up visual saliency as center surround conditional entropy and presents a fast and efficient technique for the computation of such a saliency map. It is shown that the new saliency formulation is consistent with self-information based saliency, decision-theoretic saliency and Bayesian defini... | Fast non parametric entropy estimation for spatial-temporal saliency
method | 3,717 |
Technological advances in sensor manufacture, communication, and computing are stimulating the development of new applications that are transforming traditional vision systems into pervasive intelligent camera networks. The analysis of visual cues in multi-camera networks enables a wide range of applications, from smar... | Sparse Camera Network for Visual Surveillance -- A Comprehensive Survey | 3,718 |
For nonrigid image registration, matching the particular structures (or the outliers) that have missing correspondence and/or local large deformations, can be more difficult than matching the common structures with small deformations in the two images. Most existing works depend heavily on the outlier segmentation to r... | Local Structure Matching Driven by Joint-Saliency-Structure Adaptive
Kernel Regression | 3,719 |
Bottom-up saliency, an early human visual processing, behaves like binary classification of interest and null hypothesis. Its discriminant power, mutual information of image features and class distribution, is closely related to saliency value by the well-known centre-surround theory. As classification accuracy very mu... | Multi-scale Visual Attention & Saliency Modelling with Decision Theory | 3,720 |
Image denoising is one of the fundamental problems in image processing. In this paper, a novel approach to suppress noise from the image is conducted by applying the interquartile range (IQR) which is one of the statistical methods used to detect outlier effect from a dataset. A window of size kXk was implemented to su... | Image Denoising Using Interquartile Range Filter with Local Averaging | 3,721 |
Image interpolation has been used spaciously by customary interpolation techniques. Recently, Kriging technique has been widely implemented in simulation area and geostatistics for prediction. In this article, Kriging technique was used instead of the classical interpolation methods to predict the unknown points in the... | Image Interpolation Using Kriging Technique for Spatial Data | 3,722 |
Image thresholding has played an important role in image segmentation. This paper presents a hybrid approach for image segmentation based on the thresholding by fuzzy c-means (THFCM) algorithm for image segmentation. The goal of the proposed approach is to find a discerner cluster able to find an automatic threshold. T... | Hybrid Image Segmentation using Discerner Cluster in FCM and Histogram
Thresholding | 3,723 |
Image denoising is a critical issue in the field of digital image processing. This paper proposes a novel Salt & Pepper noise suppression by developing a Kriging Interpolation Filter (KIF) for image denoising. Gray-level images degraded with Salt & Pepper noise have been considered. A sequential search for noise detect... | Kriging Interpolation Filter to Reduce High Density Salt and Pepper
Noise | 3,724 |
We present a fast algorithm for training MaxPooling Convolutional Networks to segment images. This type of network yields record-breaking performance in a variety of tasks, but is normally trained on a computationally expensive patch-by-patch basis. Our new method processes each training image in a single pass, which i... | A Fast Learning Algorithm for Image Segmentation with Max-Pooling
Convolutional Networks | 3,725 |
An increasing number of methods for background subtraction use Robust PCA to identify sparse foreground objects. While many algorithms use the L1-norm as a convex relaxation of the ideal sparsifying function, we approach the problem with a smoothed Lp-norm and present pROST, a method for robust online subspace tracking... | pROST : A Smoothed Lp-norm Robust Online Subspace Tracking Method for
Realtime Background Subtraction in Video | 3,726 |
The limitations of conventional imaging techniques have hitherto precluded a thorough and formal investigation of the complex morphology of the left ventricular (LV) endocardial surface and its relation to the severity of Coronary Artery Disease (CAD). Recent developments in high-resolution Multirow-Detector Computed T... | Morphological Analusis Of The Left Ventricular Eendocardial Surface
Using A Bag-Of-Features Descriptor | 3,727 |
We present a performance analysis for image registration with gradient descent methods. We consider a typical multiscale registration setting where the global 2-D translation between a pair of images is estimated by smoothing the images and minimizing the distance between them with gradient descent. Our study particula... | Analysis of Descent-Based Image Registration | 3,728 |
In photography, low depth of field (DOF) is an important technique to emphasize the object of interest (OOI) within an image. Thus, low DOF images are widely used in the application area of macro, portrait or sports photography. When viewing a low DOF image, the viewer implicitly concentrates on the regions that are sh... | Robust Image Segmentation in Low Depth Of Field Images | 3,729 |
Iris recognition, a relatively new biometric technology, has great advantages, such as variability, stability and security, thus is the most promising for high security environment. Iris recognition is proposed in this report. We describe some methods, the first one is based on grey level histogram to extract the pupil... | A new scheme of signature extraction for iris authentication | 3,730 |
Recognition is the fundamental task of visual cognition, yet how to formalize the general recognition problem for computer vision remains an open issue. The problem is sometimes reduced to the simplest case of recognizing matching pairs, often structured to allow for metric constraints. However, visual recognition is b... | Good Recognition is Non-Metric | 3,731 |
Object detection and recognition are important problems in computer vision. Since these problems are meta-heuristic, despite a lot of research, practically usable, intelligent, real-time, and dynamic object detection/recognition methods are still unavailable. We propose a new object detection/recognition method, which ... | Object Detection in Real Images | 3,732 |
Shape is one of the main features in content based image retrieval (CBIR). This paper proposes a new shape signature. In this technique, features of each shape are extracted based on four sides of the rectangle that covers the shape. The proposed technique is Fourier based and it is invariant to translation, scaling an... | Four Side Distance: A New Fourier Shape Signature | 3,733 |
In this paper, we derive new shape descriptors based on a directional characterization. The main idea is to study the behavior of the shape neighborhood under family of transformations. We obtain a description invariant with respect to rotation, reflection, translation and scaling. A well-defined metric is then propose... | Shape Characterization via Boundary Distortion | 3,734 |
Human labeled datasets, along with their corresponding evaluation algorithms, play an important role in boundary detection. We here present a psychophysical experiment that addresses the reliability of such benchmarks. To find better remedies to evaluate the performance of any boundary detection algorithm, we propose a... | A Meta-Theory of Boundary Detection Benchmarks | 3,735 |
Face recognition from image or video is a popular topic in biometrics research. Many public places usually have surveillance cameras for video capture and these cameras have their significant value for security purpose. It is widely acknowledged that the face recognition have played an important role in surveillance sy... | Image-based Face Detection and Recognition: "State of the Art" | 3,736 |
Sparse representations with learned dictionaries have been successful in several image analysis applications. In this paper, we propose and analyze the framework of ensemble sparse models, and demonstrate their utility in image restoration and unsupervised clustering. The proposed ensemble model approximates the data a... | Ensemble Sparse Models for Image Analysis | 3,737 |
In this paper, we propose a method to apply the popular cascade classifier into face recognition to improve the computational efficiency while keeping high recognition rate. In large scale face recognition systems, because the probability of feature templates coming from different subjects is very high, most of the mat... | Fast Matching by 2 Lines of Code for Large Scale Face Recognition
Systems | 3,738 |
Joint saliency map (JSM) [1] was developed to assign high joint saliency values to the corresponding saliency structures (called Joint Saliency Structures, JSSs) but zero or low joint saliency values to the outliers (or mismatches) that are introduced by missing correspondence or local large deformations between the re... | Scale Selection of Adaptive Kernel Regression by Joint Saliency Map for
Nonrigid Image Registration | 3,739 |
In complex visual recognition tasks it is typical to adopt multiple descriptors, that describe different aspects of the images, for obtaining an improved recognition performance. Descriptors that have diverse forms can be fused into a unified feature space in a principled manner using kernel methods. Sparse models that... | Multiple Kernel Sparse Representations for Supervised and Unsupervised
Learning | 3,740 |
Driven by the significant advancements in technology and social issues such as security management, there is a strong need for Smart Surveillance System in our society today. One of the key features of a Smart Surveillance System is efficient human detection and counting such that the system can decide and label events... | Omega Model for Human Detection and Counting for application in Smart
Surveillance System | 3,741 |
Sign Language Recognition is one of the most growing fields of research today. Many new techniques have been developed recently in these fields. Here in this paper, we have proposed a system using Eigen value weighted Euclidean distance as a classification technique for recognition of various Sign Languages of India. T... | Indian Sign Language Recognition Using Eigen Value Weighted Euclidean
Distance Based Classification Technique | 3,742 |
In this paper, an Eigenvector based system has been presented to recognize facial expressions from digital facial images. In the approach, firstly the images were acquired and cropping of five significant portions from the image was performed to extract and store the Eigenvectors specific to the expressions. The Eigenv... | Recognition of Facial Expression Using Eigenvector Based Distributed
Features and Euclidean Distance Based Decision Making Technique | 3,743 |
Medical image segmentation is referred to the segmentation of known anatomic structures from different medical images. Normally, the medical data researches are more complicated and an exclusive structures. This computer aided diagnosis is used for assisting doctors in evaluating medical imagery or in recognizing abnor... | Automatic symmetry based cluster approach for anomalous brain
identification in PET scan image : An Analysis | 3,744 |
Recognition of epileptic focal point is the important diagnosis when screening the epilepsy patients for latent surgical cures. The accurate localization is challenging one because of the low spatial resolution images with more noisy data. Positron Emission Tomography (PET) has now replaced the issues and caring a high... | Symmetry Based Cluster Approach for Automatic Recognition of the
Epileptic Focus in Brain Using PET Scan Image : An Analysis | 3,745 |
Nuclear image has emerged as a promising research work in medical field. Images from different modality meet its own challenge. Positron Emission Tomography (PET) image may help to precisely localize disease to assist in planning the right treatment for each case and saving valuable time. In this paper, a novel approac... | Spatial Fuzzy C Means PET Image Segmentation of Neurodegenerative
Disorder | 3,746 |
Volumetric change in glioblastoma multiforme (GBM) over time is a critical factor in treatment decisions. Typically, the tumor volume is computed on a slice-by-slice basis using MRI scans obtained at regular intervals. (3D)Slicer - a free platform for biomedical research - provides an alternative to this manual slice-b... | GBM Volumetry using the 3D Slicer Medical Image Computing Platform | 3,747 |
In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has suffi... | On Robust Face Recognition via Sparse Encoding: the Good, the Bad, and
the Ugly | 3,748 |
This paper presents a new approach for the automatic license plate recognition, which includes the SIFT algorithm in step to locate the plate in the input image. In this new approach, besides the comparison of the features obtained with the SIFT algorithm, the correspondence between the spatial orientations and the pos... | ALPRS - A New Approach for License Plate Recognition using the Sift
Algorithm | 3,749 |
Energies with high-order non-submodular interactions have been shown to be very useful in vision due to their high modeling power. Optimization of such energies, however, is generally NP-hard. A naive approach that works for small problem instances is exhaustive search, that is, enumeration of all possible labelings of... | Simplifying Energy Optimization using Partial Enumeration | 3,750 |
This paper is devoted to improve automatic emotion recognition from speech by incorporating rhythm and temporal features. Research on automatic emotion recognition so far has mostly been based on applying features like MFCCs, pitch and energy or intensity. The idea focuses on borrowing rhythm features from linguistic a... | Improving Automatic Emotion Recognition from speech using Rhythm and
Temporal feature | 3,751 |
Signal space models in both phase-encode, and frequency-encode directions are presented for extrapolation of 2D partial kspace. Using the boxcar representation of low-resolution spatial data, and a geometrical representation of signal space vectors in both positive and negative phase-encode directions, a robust predict... | Least-Squares FIR Models of Low-Resolution MR data for Efficient
Phase-Error Compensation with Simultaneous Artefact Removal | 3,752 |
We present an edge preserving and denoising filter for enhancing the features in images, which contain an ROI having a narrow spatial extent. Typical examples include angiograms, or ROI spatially distributed in multiple locations and contained within an outlying region, such as in multiple-sclerosis. The filtering invo... | Voxel-wise Weighted MR Image Enhancement using an Extended Neighborhood
Filter | 3,753 |
For the purposes of foreground estimation, the true background model is unavailable in many practical circumstances and needs to be estimated from cluttered image sequences. We propose a sequential technique for static background estimation in such conditions, with low computational and memory requirements. Image seque... | A Low-Complexity Algorithm for Static Background Estimation from
Cluttered Image Sequences in Surveillance Contexts | 3,754 |
Many standard approaches for geometric model fitting are based on pre-matched image features. Typically, such pre-matching uses only feature appearances (e.g. SIFT) and a large number of non-unique features must be discarded in order to control the false positive rate. In contrast, we solve feature matching and multi-m... | Joint optimization of fitting & matching in multi-view reconstruction | 3,755 |
In this paper, we propose sparse coding-based approaches for segmentation of tumor regions from MR images. Sparse coding with data-adapted dictionaries has been successfully employed in several image recovery and vision problems. The proposed approaches obtain sparse codes for each pixel in brain magnetic resonance ima... | Kernel Sparse Models for Automated Tumor Segmentation | 3,756 |
In this paper we study the bilateral filter proposed by Tomasi and Manduchi, as a spectral domain transform defined on a weighted graph. The nodes of this graph represent the pixels in the image and a graph signal defined on the nodes represents the intensity values. Edge weights in the graph correspond to the bilatera... | Bilateral Filter: Graph Spectral Interpretation and Extensions | 3,757 |
This paper presents a Gaussian Mixture Model (GMM) to identify the script of handwritten words of Roman, Devanagari, Kannada and Telugu scripts. It emphasizes the significance of directional energies for identification of script of the word. It is robust to varied image sizes and different styles of writing. A GMM is m... | Gaussian Mixture Model for Handwritten Script Identification | 3,758 |
In contrast to comparing faces via single exemplars, matching sets of face images increases robustness and discrimination performance. Recent image set matching approaches typically measure similarities between subspaces or manifolds, while representing faces in a rigid and holistic manner. Such representations are eas... | Combined Learning of Salient Local Descriptors and Distance Metrics for
Image Set Face Verification | 3,759 |
We consider object detection using a generic model for natural shapes. A common approach for object recognition involves matching object models directly to images. Another approach involves building intermediate representations via a generic grouping processes. We argue that these two processes (model-based recognition... | A Stochastic Grammar for Natural Shapes | 3,760 |
In this paper, we use statistical texture features for handwritten and printed text classification. We primarily aim for word level classification in south Indian scripts. Words are first extracted from the scanned document. For each extracted word, statistical texture features are computed such as mean, standard devia... | Statistical Texture Features based Handwritten and Printed Text
Classification in South Indian Documents | 3,761 |
In this paper, we propose a novel approach for texture analysis based on artificial crawler model. Our method assumes that each agent can interact with the environment and each other. The evolution process converges to an equilibrium state according to the set of rules. For each textured image, the feature vector is co... | Material quality assessment of silk nanofibers based on swarm
intelligence | 3,762 |
Background subtraction is a fundamental low-level processing task in numerous computer vision applications. The vast majority of algorithms process images on a pixel-by-pixel basis, where an independent decision is made for each pixel. A general limitation of such processing is that rich contextual information is not t... | Improved Foreground Detection via Block-based Classifier Cascade with
Probabilistic Decision Integration | 3,763 |
The aim of the paper is to separate handwritten and printed text from a real document embedded with noise, graphics including annotations. Relying on run-length smoothing algorithm (RLSA), the extracted pseudo-lines and pseudo-words are used as basic blocks for classification. To handle this, a multi-class support vect... | Handwritten and Printed Text Separation in Real Document | 3,764 |
Visual object tracking is a significant computer vision task which can be applied to many domains such as visual surveillance, human computer interaction, and video compression. In the literature, researchers have proposed a variety of 2D appearance models. To help readers swiftly learn the recent advances in 2D appear... | A Survey of Appearance Models in Visual Object Tracking | 3,765 |
Handwriting recognition refers to the identification of written characters. Handwriting recognition has become an acute research area in recent years for the ease of access of computer science. In this paper primarily discussed On-line and Off-line handwriting recognition methods for Arabic words which are often used a... | The State of the Art Recognize in Arabic Script through Combination of
Online and Offline | 3,766 |
A variety of operations of cellular automata on gray images is presented. All operations are of a wave-front nature finishing in a stable state. They are used to extract shape descripting gray objects robust to a variety of pattern distortions. Topographic terms are used: "lakes", "dales", "dales of dales". It is shown... | Asynchronous Cellular Operations on Gray Images Extracting Topographic
Shape Features and Their Relations | 3,767 |
We proposed an algorithm for solving Hamilton-Jacobi equation associated to an optimal trajectory problem for a vehicle moving inside the pre-specified domain with the speed depending upon the direction of the motion and current position of the vehicle. The dynamics of the vehicle is defined by an ordinary differential... | On Constructing the Value Function for Optimal Trajectory Problem and
its Application to Image Processing | 3,768 |
This paper describes a novel method for partitioning image into meaningful segments. The proposed method employs watershed transform, a well-known image segmentation technique. Along with that, it uses various auxiliary schemes such as Binary Gradient Masking, dilation which segment the image in proper way. The algorit... | A Robust Rapid Approach to Image Segmentation with Optimal Thresholding
and Watershed Transform | 3,769 |
Brain shift, i.e. the change in configuration of the brain after opening the dura mater, is a key problem in neuronavigation. We present an approach to co-register intra-operative microscope images with pre-operative MRI to adapt and optimize intra-operative neuronavigation. The tools are a robust classification of sul... | Cortical Surface Co-Registration based on MRI Images and Photos | 3,770 |
Cascade classifiers are one of the most important contributions to real-time object detection. Nonetheless, there are many challenging problems arising in training cascade detectors. One common issue is that the node classifier is trained with a symmetric classifier. Having a low misclassification error rate does not g... | Asymmetric Pruning for Learning Cascade Detectors | 3,771 |
Many interpolation methods have been developed for high visual quality, but fail for inability to preserve image structures. Edges carry heavy structural information for detection, determination and classification. Edge-adaptive interpolation approaches become a center of focus. In this paper, performance of four edge-... | Performance Evaluation of Edge-Directed Interpolation Methods for Images | 3,772 |
Remote sensing techniques are widely used for land cover classification and urban analysis. The availability of high resolution remote sensing imagery limits the level of classification accuracy attainable from pixel-based approach. In this paper object-based classification scheme based on a hierarchical support vector... | An N-dimensional approach towards object based classification of
remotely sensed imagery | 3,773 |
Automatic feature extraction domain has witnessed the application of many intelligent methodologies over past decade; however detection accuracy of these approaches were limited as object geometry and contextual knowledge were not given enough consideration. In this paper, we propose a frame work for accurate detection... | An intelligent approach towards automatic shape modeling and object
extraction from satellite images using cellular automata based algorithm | 3,774 |
Entropy is the measure of uncertainty in any data and is adopted for maximisation of mutual information in many remote sensing operations. The availability of wide entropy variations motivated us for an investigation over the suitability preference of these versions to specific operations. Methodologies were implemente... | A Comparative Analysis on the Applicability of Entropy in remote sensing | 3,775 |
Image registration is the process of transforming different sets of data into one coordinate system and is required for various remote sensing applications like change detection, image fusion, and other related areas. The effect of increased relief displacement, requirement of more control points, and increased data vo... | An investigation towards wavelet based optimization of automatic image
registration techniques | 3,776 |
Methodological contributions: This paper introduces a family of kernels for analyzing (anatomical) trees endowed with vector valued measurements made along the tree. While state-of-the-art graph and tree kernels use combinatorial tree/graph structure with discrete node and edge labels, the kernels presented in this pap... | Geometric tree kernels: Classification of COPD from airway tree geometry | 3,777 |
This work presents an automatic human gender and age group recognition system based on human facial images. It makes an extensive experiment with row pixel intensity valued features and Discrete Cosine Transform (DCT) coefficient features with Principal Component Analysis and k-Nearest Neighbor classification to identi... | Age group and gender recognition from human facial images | 3,778 |
The two-dimensional Gabor function is adapted to natural image statistics, leading to a tractable probabilistic generative model that can be used to model simple-cell receptive-field profiles, or generate basis functions for sparse coding applications. Learning is found to be most pronounced in three Gabor-function par... | The two-dimensional Gabor function adapted to natural image statistics:
A model of simple-cell receptive fields and sparse structure in images | 3,779 |
Human eye can see and read what is written or displayed either in natural handwriting or in printed format. The same work in case the machine does is called handwriting recognition. Handwriting recognition can be broken down into two categories: off-line and on-line. ... | Stroke-Based Cursive Character Recognition | 3,780 |
We present an image representation method which is derived from analyzing Gaussian probability density function (\emph{pdf}) space using Lie group theory. In our proposed method, images are modeled by Gaussian mixture models (GMMs) which are adapted from a globally trained GMM called universal background model (UBM). T... | Lie Algebrized Gaussians for Image Representation | 3,781 |
A new multiscale implementation of non-local means filtering for image denoising is proposed. The proposed algorithm also introduces a modification of similarity measure for patch comparison. The standard Euclidean norm is replaced by weighted Euclidean norm for patch based comparison. Assuming the patch as an oriented... | Multiscale Hybrid Non-local Means Filtering Using Modified Similarity
Measure | 3,782 |
A robust and efficient anomaly detection technique is proposed, capable of dealing with crowded scenes where traditional tracking based approaches tend to fail. Initial foreground segmentation of the input frames confines the analysis to foreground objects and effectively ignores irrelevant background dynamics. Input f... | Improved Anomaly Detection in Crowded Scenes via Cell-based Analysis of
Foreground Speed, Size and Texture | 3,783 |
The study and development of software able to show the effect of aging of faces is one of the tasks of face recognition technologies. Some software solutions are used for investigations, some others to show the effects of drugs on healthy appearance, however some other applications can be proposed for the analysis of v... | A software for aging faces applied to ancient marble busts | 3,784 |
Barten's model of spatio-temporal contrast sensitivity function of human visual system is embedded in a multi-slice channelized Hotelling observer. This is done by 3D filtering of the stack of images with the spatio-temporal contrast sensitivity function and feeding the result (i.e., the perceived image stack) to the m... | Integration of spatio-temporal contrast sensitivity with a multi-slice
channelized Hotelling observer | 3,785 |
This work proposes the combination of multiscale transform with fractal descriptors employed in the classification of gray-level texture images. We apply the space-scale transform (derivative + Gaussian filter) over the Bouligand-Minkowski fractal descriptors, followed by a threshold over the filter response, aiming at... | Multiscale Fractal Descriptors Applied to Texture Classification | 3,786 |
In this paper, we consider the approximate weighted graph matching problem and introduce stable and informative first and second order compatibility terms suitable for inclusion into the popular integer quadratic program formulation. Our approach relies on a rigorous analysis of stability of spectral signatures based o... | Stable and Informative Spectral Signatures for Graph Matching | 3,787 |
Some software solutions used to obtain the facial transformations can help investigating the artistic metamorphosis of the ancient portraits of the same person. An analysis with a freely available software of portraitures of Julius Caesar is proposed, showing his several "morphs". The software helps enhancing the mood ... | Facial transformations of ancient portraits: the face of Caesar | 3,788 |
Extracting minutiae from fingerprint images is one of the most important steps in automatic fingerprint identification system. Because minutiae matching are certainly the most well-known and widely used method for fingerprint matching, minutiae are local discontinuities in the fingerprint pattern. In this paper a finge... | Automatic Fingerprint Recognition Using Minutiae Matching Technique for
the Large Fingerprint Database | 3,789 |
Dimensionality reduction (DR) of image features plays an important role in image retrieval and classification tasks. Recently, two types of methods have been proposed to improve the both the accuracy and efficiency for the dimensionality reduction problem. One uses Non-negative matrix factorization (NMF) to describe th... | Image Classification by Feature Dimension Reduction and Graph based
Ranking | 3,790 |
We present a new approach to rigid-body motion segmentation from two views. We use a previously developed nonlinear embedding of two-view point correspondences into a 9-dimensional space and identify the different motions by segmenting lower-dimensional subspaces. In order to overcome nonuniform distributions along the... | A New Approach To Two-View Motion Segmentation Using Global Dimension
Minimization | 3,791 |
Recognizing 3D objects in the presence of noise, varying mesh resolution, occlusion and clutter is a very challenging task. This paper presents a novel method named Rotational Projection Statistics (RoPS). It has three major modules: Local Reference Frame (LRF) definition, RoPS feature description and 3D object recogni... | Rotational Projection Statistics for 3D Local Surface Description and
Object Recognition | 3,792 |
We describe a non-parametric, "example-based" method for estimating the depth of an object, viewed in a single photo. Our method consults a database of example 3D geometries, searching for those which look similar to the object in the photo. The known depths of the selected database objects act as shape priors which co... | Single View Depth Estimation from Examples | 3,793 |
Accurate detection of mitosis plays a critical role in breast cancer histopathology. Manual detection and counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. Multispectral imaging is a recent medical imaging technology, proven successful in increasing the segmentation accuracy... | Multispectral Spatial Characterization: Application to Mitosis Detection
in Breast Cancer Histopathology | 3,794 |
Recovering shadows is an important step for many vision algorithms. Current approaches that work with time-lapse sequences are limited to simple thresholding heuristics. We show these approaches only work with very careful tuning of parameters, and do not work well for long-term time-lapse sequences taken over the span... | Shadow Estimation Method for "The Episolar Constraint: Monocular Shape
from Shadow Correspondence" | 3,795 |
Some mixtures, such as colloids like milk, blood, and gelatin, have homogeneous appearance when viewed with the naked eye, however, to observe them at the nanoscale is possible to understand the heterogeneity of its components. The same phenomenon can occur in pattern recognition in which it is possible to see heteroge... | Heterogeneous patterns enhancing static and dynamic texture
classification | 3,796 |
Hand Gesture is a popular way to interact or control machines and it has been implemented in many applications. The geometry of hand is such that it is hard to construct in virtual environment and control the joints but the functionality and DOF encourage researchers to make a hand like instrument. This paper presents ... | Tracking of Fingertips and Centres of Palm using KINECT | 3,797 |
In Computer Vision, colour-based spatial techniquesoften assume a static skin colour model. However, skin colour perceived by a camera can change when lighting changes. In common real environment multiple light sources impinge on the skin. Moreover, detection techniques may vary when the image under study is taken unde... | Automated Switching System for Skin Pixel Segmentation in Varied
Lighting | 3,798 |
Image sequences filtering have recently become a very important technical problem especially with the advent of new technology in multimedia and video systems applications. Often image sequences are corrupted by some amount of noise introduced by the image sensor and therefore inherently present in the imaging process.... | Robust Noise Filtering in Image Sequences | 3,799 |
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