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Various and different methods can be used to produce high-resolution multispectral images from high-resolution panchromatic image (PAN) and low-resolution multispectral images (MS), mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its original images. There is also ... | Studying Satellite Image Quality Based on the Fusion Techniques | 3,400 |
The paper will present a novel approach for solving face recognition problem. Our method combines 2D Principal Component Analysis (2DPCA), one of the prominent methods for extracting feature vectors, and Support Vector Machine (SVM), the most powerful discriminative method for classification. Experiments based on propo... | Face Recognition Based on SVM and 2DPCA | 3,401 |
Fast and robust hand segmentation and tracking is an essential basis for gesture recognition and thus an important component for contact-less human-computer interaction (HCI). Hand gesture recognition based on 2D video data has been intensively investigated. However, in practical scenarios purely intensity based approa... | Hand Tracking based on Hierarchical Clustering of Range Data | 3,402 |
The acquisition of MRI images offers a trade-off in terms of acquisition time, spatial/temporal resolution and signal-to-noise ratio (SNR). Thus, for instance, increasing the time efficiency of MRI often comes at the expense of reduced SNR. This, in turn, necessitates the use of post-processing tools for noise rejectio... | A New Similarity Measure for Non-Local Means Filtering of MRI Images | 3,403 |
Spectral unmixing is an important tool in hyperspectral data analysis for estimating endmembers and abundance fractions in a mixed pixel. This paper examines the applicability of a recently developed algorithm called graph regularized nonnegative matrix factorization (GNMF) for this aim. The proposed approach exploits ... | Graph Regularized Nonnegative Matrix Factorization for Hyperspectral
Data Unmixing | 3,404 |
This report concerns the use of techniques for sparse signal representation and sparse error correction for automatic face recognition. Much of the recent interest in these techniques comes from the paper "Robust Face Recognition via Sparse Representation" by Wright et al. (2009), which showed how, under certain techni... | Sparsity and Robustness in Face Recognition | 3,405 |
Extending the Liouville-Caputo definition of a fractional derivative to a nonlocal covariant generalization of arbitrary bound operators acting on multidimensional Riemannian spaces an appropriate approach for the 3D shape recovery of aperture afflicted 2D slide sequences is proposed. We demonstrate, that the step from... | Covariant fractional extension of the modified Laplace-operator used in
3D-shape recovery | 3,406 |
Many applications require comparing multimodal data with different structure and dimensionality that cannot be compared directly. Recently, there has been increasing interest in methods for learning and efficiently representing such multimodal similarity. In this paper, we present a simple algorithm for multimodal simi... | Multimodal diff-hash | 3,407 |
Iris recognition is considered as one of the best biometric methods used for human identification and verification, this is because of its unique features that differ from one person to another, and its importance in the security field. This paper proposes an algorithm for iris recognition and classification using a sy... | Iris Recognition Based on LBP and Combined LVQ Classifier | 3,408 |
Object detection and classification using video is necessary for intelligent planning and navigation on a mobile robot. However, current methods can be too slow or not sufficient for distinguishing multiple classes. Techniques that rely on binary (foreground/background) labels incorrectly identify areas with multiple o... | Efficient Hierarchical Markov Random Fields for Object Detection on a
Mobile Robot | 3,409 |
The recent technological progress in acquisition, modeling and processing of 3D data leads to the proliferation of a large number of 3D objects databases. Consequently, the techniques used for content based 3D retrieval has become necessary. In this paper, we introduce a new method for 3D objects recognition and retrie... | New Method for 3D Shape Retrieval | 3,410 |
A key recent advance in face recognition models a test face image as a sparse linear combination of a set of training face images. The resulting sparse representations have been shown to possess robustness against a variety of distortions like random pixel corruption, occlusion and disguise. This approach however makes... | Discriminative Local Sparse Representations for Robust Face Recognition | 3,411 |
Texture is an important spatial feature which plays a vital role in content based image retrieval. The enormous growth of the internet and the wide use of digital data have increased the need for both efficient image database creation and retrieval procedure. This paper describes a new approach for texture classificati... | A Novel Approach to Texture classification using statistical feature | 3,412 |
In this text we show, that the notion of a "good pair" that was introduced in the paper "Digital Manifolds and the Theorem of Jordan-Brouwer" has actually known models. We will show, how to choose cubical adjacencies, the generalizations of the well known 4- and 8-neighborhood to arbitrary dimensions, in order to find ... | Good Pairs of Adjacency Relations in Arbitrary Dimensions | 3,413 |
Facial Expression Classification is an interesting research problem in recent years. There are a lot of methods to solve this problem. In this research, we propose a novel approach using Canny, Principal Component Analysis (PCA) and Artificial Neural Network. Firstly, in preprocessing phase, we use Canny for local regi... | A Facial Expression Classification System Integrating Canny, Principal
Component Analysis and Artificial Neural Network | 3,414 |
In this paper a novel approach is proposed based on single Euler number feature which is free from thinning and size normalization for multi-font and multi-size Kannada numeral recognition system. A nearest neighbor classification is used for classification of Kannada numerals by considering the Euclidian distance. A t... | A Single Euler Number Feature for Multi-font Multi-size Kannada Numeral
Recognition | 3,415 |
In this paper a fast and novel method is proposed for multi-font multi-size Kannada numeral recognition which is thinning free and without size normalization approach. The different structural feature are used for numeral recognition namely, directional density of pixels in four directions, water reservoirs, maximum pr... | Multi-font Multi-size Kannada Numeral Recognition Based on Structural
Features | 3,416 |
In this paper, we propose a new redundant wavelet transform applicable to scalar functions defined on high dimensional coordinates, weighted graphs and networks. The proposed transform utilizes the distances between the given data points. We modify the filter-bank decomposition scheme of the redundant wavelet transform... | Redundant Wavelets on Graphs and High Dimensional Data Clouds | 3,417 |
One of the most famous drawings by Leonardo da Vinci is a self-portrait in red chalk, where he looks quite old. In fact, there is a sketch in one of his notebooks, partially covered by written notes, that can be a self-portrait of the artist when he was young. The use of image processing, to remove the handwritten text... | A self-portrait of young Leonardo | 3,418 |
This report is about facial asymmetry, its connection to emotional expression, and methods of measuring facial asymmetry in videos of faces. The research was motivated by two factors: firstly, there was a real opportunity to develop a novel measure of asymmetry that required minimal human involvement and that improved ... | Facial Asymmetry and Emotional Expression | 3,419 |
An image articulation manifold (IAM) is the collection of images formed when an object is articulated in front of a camera. IAMs arise in a variety of image processing and computer vision applications, where they provide a natural low-dimensional embedding of the collection of high-dimensional images. To date IAMs have... | A Theory for Optical flow-based Transport on Image Manifolds | 3,420 |
In many image processing applications, such as segmentation and classification, the selection of robust features descriptors is crucial to improve the discrimination capabilities in real world scenarios. In particular, it is well known that image textures constitute power visual cues for feature extraction and classifi... | Invariant texture analysis through Local Binary Patterns | 3,421 |
We present Local Naive Bayes Nearest Neighbor, an improvement to the NBNN image classification algorithm that increases classification accuracy and improves its ability to scale to large numbers of object classes. The key observation is that only the classes represented in the local neighborhood of a descriptor contrib... | Local Naive Bayes Nearest Neighbor for Image Classification | 3,422 |
In this paper we present a biorealistic model for the first part of the early vision processing by incorporating memristive nanodevices. The architecture of the proposed network is based on the organisation and functioning of the outer plexiform layer (OPL) in the vertebrate retina. We demonstrate that memristive devic... | A Biomimetic Model of the Outer Plexiform Layer by Incorporating
Memristive Devices | 3,423 |
We propose in this paper a tracking algorithm which is able to adapt itself to different scene contexts. A feature pool is used to compute the matching score between two detected objects. This feature pool includes 2D, 3D displacement distances, 2D sizes, color histogram, histogram of oriented gradient (HOG), color cov... | A multi-feature tracking algorithm enabling adaptation to context
variations | 3,424 |
Crucial information barely visible to the human eye is often embedded in a series of low-resolution images taken of the same scene. Super-resolution enables the extraction of this information by reconstructing a single image, at a high resolution than is present in any of the individual images. This is particularly use... | POCS Based Super-Resolution Image Reconstruction Using an Adaptive
Regularization Parameter | 3,425 |
This paper presents a novel reaction-diffusion (RD) method for implicit active contours, which is completely free of the costly re-initialization procedure in level set evolution (LSE). A diffusion term is introduced into LSE, resulting in a RD-LSE equation, to which a piecewise constant solution can be derived. In ord... | Re-initialization Free Level Set Evolution via Reaction Diffusion | 3,426 |
This paper proposes a new procedure in order to improve the performance of block matching and 3-D filtering (BM3D) image denoising algorithm. It is demonstrated that it is possible to achieve a better performance than that of BM3D algorithm in a variety of noise levels. This method changes BM3D algorithm parameter valu... | Improvement of BM3D Algorithm and Employment to Satellite and CFA Images
Denoising | 3,427 |
Clustering is a fundamental task in unsupervised learning. The focus of this paper is the Correlation Clustering functional which combines positive and negative affinities between the data points. The contribution of this paper is two fold: (i) Provide a theoretic analysis of the functional. (ii) New optimization algor... | Large Scale Correlation Clustering Optimization | 3,428 |
Matching animal-like flexibility in recognition and the ability to quickly incorporate new information remains difficult. Limits are yet to be adequately addressed in neural models and recognition algorithms. This work proposes a configuration for recognition that maintains the same function of conventional algorithms ... | Supervised Generative Reconstruction: An Efficient Way To Flexibly Store
and Recognize Patterns | 3,429 |
Combining information from various image features has become a standard technique in concept recognition tasks. However, the optimal way of fusing the resulting kernel functions is usually unknown in practical applications. Multiple kernel learning (MKL) techniques allow to determine an optimal linear combination of su... | Insights from Classifying Visual Concepts with Multiple Kernel Learning | 3,430 |
A vehicle detection plays an important role in the traffic control at signalised intersections. This paper introduces a vision-based algorithm for vehicles presence recognition in detection zones. The algorithm uses linguistic variables to evaluate local attributes of an input image. The image attributes are categorise... | A real time vehicles detection algorithm for vision based sensors | 3,431 |
In this paper a vision-based vehicles recognition method is presented. Proposed method uses fuzzy description of image segments for automatic recognition of vehicles recorded in image data. The description takes into account selected geometrical properties and shape coefficients determined for segments of reference ima... | Vehicles Recognition Using Fuzzy Descriptors of Image Segments | 3,432 |
In this paper, we introduce a Reduced Reference Image Quality Assessment (RRIQA) measure based on the natural image statistic approach. A new adaptive transform called "Tetrolet" is applied to both reference and distorted images. To model the marginal distribution of tetrolet coefficients Bessel K Forms (BKF) density i... | A Reduced Reference Image Quality Measure Using Bessel K Forms Model for
Tetrolet Coefficients | 3,433 |
A fundamental task in human chromosome analysis is chromosome segmentation. Segmentation plays an important role in chromosome karyotyping. The first step in segmentation is to remove intrusive objects such as stain debris and other noises. The next step is detection of touching and overlapping chromosomes, and the fin... | A Geometric Approach For Fully Automatic Chromosome Segmentation | 3,434 |
After the discovery that fixed points of loopy belief propagation coincide with stationary points of the Bethe free energy, several researchers proposed provably convergent algorithms to directly minimize the Bethe free energy. These algorithms were formulated only for non-zero temperature (thus finding fixed points of... | Zero-Temperature Limit of a Convergent Algorithm to Minimize the Bethe
Free Energy | 3,435 |
Transformation-invariant analysis of signals often requires the computation of the distance from a test pattern to a transformation manifold. In particular, the estimation of the distances between a transformed query signal and several transformation manifolds representing different classes provides essential informati... | Discretization of Parametrizable Signal Manifolds | 3,436 |
Manifold models provide low-dimensional representations that are useful for processing and analyzing data in a transformation-invariant way. In this paper, we study the problem of learning smooth pattern transformation manifolds from image sets that represent observations of geometrically transformed signals. In order ... | Learning Smooth Pattern Transformation Manifolds | 3,437 |
A framework of online adaptive statistical compressed sensing is introduced for signals following a mixture model. The scheme first uses non-adaptive measurements, from which an online decoding scheme estimates the model selection. As soon as a candidate model has been selected, an optimal sensing scheme for the select... | Online Adaptive Statistical Compressed Sensing of Gaussian Mixture
Models | 3,438 |
Personal identification problem has been a major field of research in recent years. Biometrics-based technologies that exploit fingerprints, iris, face, voice and palmprints, have been in the center of attention to solve this problem. Palmprints can be used instead of fingerprints that have been of the earliest of thes... | Multispectral Palmprint Recognition Using a Hybrid Feature | 3,439 |
Biometric based authentication for secured access to resources has gained importance, due to their reliable, invariant and discriminating features. Palmprint is one such biometric entity. Prior to classification and identification registering a sample palmprint is an important activity. In this paper we propose a compu... | Automated PolyU Palmprint sample Registration and Coarse Classification | 3,440 |
This paper presents a method for learning overcomplete dictionaries composed of two modalities that describe a 3D scene: image intensity and scene depth. We propose a novel Joint Basis Pursuit (JBP) algorithm that finds related sparse features in two modalities using conic programming and integrate it into a two-step d... | Learning joint intensity-depth sparse representations | 3,441 |
In this paper, a salient region extraction method for creating picture collage based on stereo vision is proposed. Picture collage is a kind of visual image summary to arrange all input images on a given canvas, allowing overlay, to maximize visible visual information. The salient regions of each image are firstly extr... | Picture Collage with Genetic Algorithm and Stereo vision | 3,442 |
A uniform distribution of the image force field around the object fasts the convergence speed of the segmentation process. However, to achieve this aim, it causes the force constructed from the heat diffusion model unable to indicate the object boundaries accurately. The image force based on electrostatic field model c... | A United Image Force for Deformable Models and Direct Transforming
Geometric Active Contorus to Snakes by Level Sets | 3,443 |
In this paper, a new adaptive noise reduction scheme for images corrupted by impulse noise is presented. The proposed scheme efficiently identifies and reduces salt and pepper noise. MAG (Mean Absolute Gradient) is used to identify pixels which are most likely corrupted by salt and pepper noise that are candidates for ... | Adaptive Noise Reduction Scheme for Salt and Pepper | 3,444 |
This paper suggests a nonparametric scheme to find the sparse solution of the underdetermined system of linear equations in the presence of unknown impulsive or non-Gaussian noise. This approach is robust against any variations of the noise model and its parameters. It is based on minimization of rank pseudo norm of th... | Nonparametric Sparse Representation | 3,445 |
Solving the Maximum a Posteriori on Markov Random Field, MRF-MAP, is a prevailing method in recent interactive image segmentation tools. Although mathematically explicit in its computational targets, and impressive for the segmentation quality, MRF-MAP is hard to accomplish without the interactive information from user... | NegCut: Automatic Image Segmentation based on MRF-MAP | 3,446 |
We present an algorithm using transformation groups and their irreducible representations to generate an orthogonal basis for a signal in the vector space of the signal. It is shown that multiresolution analysis can be done with amplitudes using a transformation group. G-lets is thus not a single transform, but a group... | G-Lets: Signal Processing Using Transformation Groups | 3,447 |
This paper presents a new method for automatic quantification of ellipse-like cells in images, an important and challenging problem that has been studied by the computer vision community. The proposed method can be described by two main steps. Initially, image segmentation based on the k-means algorithm is performed to... | Automatic system for counting cells with elliptical shape | 3,448 |
Shape is one of the most important visual attributes to characterize objects, playing a important role in pattern recognition. There are various approaches to extract relevant information of a shape. An approach widely used in shape analysis is the complexity, and Fractal Dimension and Multi-Scale Fractal Dimension are... | Fractal and Multi-Scale Fractal Dimension analysis: a comparative study
of Bouligand-Minkowski method | 3,449 |
The calculus of variations applied to the image processing requires some numerical models able to perform the variations of images and the extremization of appropriate actions. To produce the variations of images, there are several possibilities based on the brightness maps. Before a numerical model, I propose an exper... | Variations of images to increase their visibility | 3,450 |
This paper presents a new method for dynamic texture recognition based on spatiotemporal Gabor filters. Dynamic textures have emerged as a new field of investigation that extends the concept of self-similarity of texture image to the spatiotemporal domain. To model a dynamic texture, we convolve the sequence of images ... | Spatiotemporal Gabor filters: a new method for dynamic texture
recognition | 3,451 |
Essentially a biometric system is a pattern recognition system which recognizes a user by determining the authenticity of a specific anatomical or behavioral characteristic possessed by the user. With the ever increasing integration of computers and Internet into daily life style, it has become necessary to protect sen... | A Multimodal Biometric System Using Linear Discriminant Analysis For
Improved Performance | 3,452 |
The use of hierarchical Conditional Random Field model deal with the problem of labeling images . At the time of labeling a new image, selection of the nearest cluster and using the related CRF model to label this image. When one give input image, one first use the CRF model to get initial pixel labels then finding the... | Image Labeling and Segmentation using Hierarchical Conditional Random
Field Model | 3,453 |
In this paper, we present a novel, learning-based, two-step super-resolution (SR) algorithm well suited to solve the specially demanding problem of obtaining SR estimates from short image sequences. The first step, devoted to increase the sampling rate of the incoming images, is performed by fitting linear combinations... | A PCA-Based Super-Resolution Algorithm for Short Image Sequences | 3,454 |
In this study we investigate the fast image filtering algorithm based on Intro sort algorithm and fast noise reduction of infrared images. Main feature of the proposed approach is that no prior knowledge of noise required. It is developed based on Stefan- Boltzmann law and the Fourier law. We also investigate the fast ... | A Novel Approach to Fast Image Filtering Algorithm of Infrared Images
based on Intro Sort Algorithm | 3,455 |
Texture analysis is an important field of investigation that has received a great deal of interest from computer vision community. In this paper, we propose a novel approach for texture modeling based on partial differential equation (PDE). Each image $f$ is decomposed into a family of derived sub-images. $f$ is split ... | Image decomposition with anisotropic diffusion applied to leaf-texture
analysis | 3,456 |
Compressive sensing (CS) is a new approach for the acquisition and recovery of sparse signals and images that enables sampling rates significantly below the classical Nyquist rate. Despite significant progress in the theory and methods of CS, little headway has been made in compressive video acquisition and recovery. V... | Compressive Acquisition of Dynamic Scenes | 3,457 |
Image binarization is the process of separation of pixel values into two groups, white as background and black as foreground. Thresholding plays a major in binarization of images. Thresholding can be categorized into global thresholding and local thresholding. In images with uniform contrast distribution of background ... | A New Local Adaptive Thresholding Technique in Binarization | 3,458 |
A framework for adaptive and non-adaptive statistical compressive sensing is developed, where a statistical model replaces the standard sparsity model of classical compressive sensing. We propose within this framework optimal task-specific sensing protocols specifically and jointly designed for classification and recon... | Task-Driven Adaptive Statistical Compressive Sensing of Gaussian Mixture
Models | 3,459 |
The appearance of microcalcifications in mammograms is one of the early signs of breast cancer. So, early detection of microcalcification clusters (MCCs) in mammograms can be helpful for cancer diagnosis and better treatment of breast cancer. In this paper a computer method has been proposed to support radiologists in ... | Comparing Methods for segmentation of Microcalcification Clusters in
Digitized Mammograms | 3,460 |
The watershed is one of the most used tools in image segmentation. We present how its concept is born and developed over time. Its implementation as an algorithm or a hardwired device evolved together with the technology which allowed it. We present also how it is used in practice, first together with markers, and late... | The watershed concept and its use in segmentation : a brief history | 3,461 |
Speeded Up Robust Features (SURF) has emerged as one of the more popular feature descriptors and detectors in recent years. Performance and algorithmic details vary widely between implementations due to SURF's complexity and ambiguities found in its description. To resolve these ambiguities, a set of general techniques... | Resolving Implementation Ambiguity and Improving SURF | 3,462 |
In this paper, we compare various image background subtraction algorithms with the ground truth of cars counted. We have given a sample of thousand images, which are the snap shots of current traffic as records at various intersections and highways. We have also counted an approximate number of cars that are visible in... | Comparing Background Subtraction Algorithms and Method of Car Counting | 3,463 |
In this paper, the inverse problem of reconstructing reflectivity function of a medium is examined within a blind deconvolution framework. The ultrasound pulse is estimated using higher-order statistics, and Wiener filter is used to obtain the ultrasonic reflectivity function through wavelet-based models. A new approac... | Wavelet-based deconvolution of ultrasonic signals in nondestructive
evaluation | 3,464 |
Determining optimal number of clusters in a dataset is a challenging task. Though some methods are available, there is no algorithm that produces unique clustering solution. The paper proposes an Automatic Merging for Single Optimal Solution (AMSOS) which aims to generate unique and nearly optimal clusters for the give... | Automatic Clustering with Single Optimal Solution | 3,465 |
This chapter shows that combining Haar-Hilbert and Log-Gabor improves iris recognition performance leading to a less ambiguous biometric decision landscape in which the overlap between the experimental intra- and interclass score distributions diminishes or even vanishes. Haar-Hilbert, Log-Gabor and combined Haar-Hilbe... | Combined Haar-Hilbert and Log-Gabor Based Iris Encoders | 3,466 |
The problem of segmenting a given image into coherent regions is important in Computer Vision and many industrial applications require segmenting a known object into its components. Examples include identifying individual parts of a component for process control work in a manufacturing plant and identifying parts of a ... | 3D Model Assisted Image Segmentation | 3,467 |
Context-dependence in human cognition process is a well-established fact. Following this, we introduced the image segmentation method that can use context to classify a pixel on the basis of its membership to a particular object-class of the concerned image. In the broad methodological steps, each pixel was defined by ... | Non-parametric convolution based image-segmentation of ill-posed objects
applying context window approach | 3,468 |
A method is developed to distinguish between cars and trucks present in a video feed of a highway. The method builds upon previously done work using covariance matrices as an accurate descriptor for regions. Background subtraction and other similar proven image processing techniques are used to identify the regions whe... | Using Covariance Matrices as Feature Descriptors for Vehicle Detection
from a Fixed Camera | 3,469 |
An innovative way of calculating the von Mises distribution (VMD) of image entropy is introduced in this paper. The VMD's concentration parameter and some fitness parameter that will be later defined, have been analyzed in the experimental part for determining their suitability as a image quality assessment measure in ... | No-reference image quality assessment through the von Mises distribution | 3,470 |
Boundary detection is essential for a variety of computer vision tasks such as segmentation and recognition. In this paper we propose a unified formulation and a novel algorithm that are applicable to the detection of different types of boundaries, such as intensity edges, occlusion boundaries or object category specif... | Generalized Boundaries from Multiple Image Interpretations | 3,471 |
This paper describes a geometry based technique for feature extraction applicable to segmentation-based word recognition systems. The proposed system extracts the geometric features of the character contour. This features are based on the basic line types that forms the character skeleton. The system gives a feature ve... | A feature extraction technique based on character geometry for character
recognition | 3,472 |
At least two software packages---DARWIN, Eckerd College, and FinScan, Texas A&M---exist to facilitate the identification of cetaceans---whales, dolphins, porpoises---based upon the naturally occurring features along the edges of their dorsal fins. Such identification is useful for biological studies of population, soci... | Unsupervised Threshold for Automatic Extraction of Dolphin Dorsal Fin
Outlines from Digital Photographs in DARWIN (Digital Analysis and Recognition
of Whale Images on a Network) | 3,473 |
Recently the sparse representation based classification (SRC) has been proposed for robust face recognition (FR). In SRC, the testing image is coded as a sparse linear combination of the training samples, and the representation fidelity is measured by the l2-norm or l1-norm of the coding residual. Such a sparse coding ... | Regularized Robust Coding for Face Recognition | 3,474 |
Color image segmentation is an important topic in the image processing field. MRF-MAP is often adopted in the unsupervised segmentation methods, but their performance are far behind recent interactive segmentation tools supervised by user inputs. Furthermore, the existing related unsupervised methods also suffer from t... | A Simple Unsupervised Color Image Segmentation Method based on MRF-MAP | 3,475 |
In this work we review the basic principles of stochastic logic and propose its application to probabilistic-based pattern-recognition analysis. The proposed technique is intrinsically a parallel comparison of input data to various pre-stored categories using Bayesian techniques. We design smart pulse-based stochastic-... | Stochastic-Based Pattern Recognition Analysis | 3,476 |
We describe a method for fast approximation of sparse coding. The input space is subdivided by a binary decision tree, and we simultaneously learn a dictionary and assignment of allowed dictionary elements for each leaf of the tree. We store a lookup table with the assignments and the pseudoinverses for each node, allo... | Fast approximations to structured sparse coding and applications to
object classification | 3,477 |
3D motion tracking is a critical task in many computer vision applications. Unsupervised markerless 3D motion tracking systems determine the most relevant object in the screen and then track it by continuously estimating its projection features (center and area) from the edge image and a point inside the relevant objec... | Filling-Based Techniques Applied to Object Projection Feature Estimation | 3,478 |
3D motion tracking is a critical task in many computer vision applications. Unsupervised markerless 3D motion tracking systems determine the most relevant object in the screen and then track it by continuously estimating its projection features (center and area) from the edge image and a point inside the relevant objec... | Using Barriers to Reduce the Sensitivity to Edge Miscalculations of
Casting-Based Object Projection Feature Estimation | 3,479 |
This paper presents the Discrete Wavelet based fusion techniques for combining perceptually important image features. SPIHT (Set Partitioning in Hierarchical Trees) algorithm is an efficient method for lossy and lossless coding of fused image. This paper presents some modifications on the SPIHT algorithm. It is based o... | Image Fusion and Re-Modified SPIHT for Fused Image | 3,480 |
In practical applications, we often have to deal with high order data, such as a grayscale image and a video sequence are intrinsically 2nd-order tensor and 3rd-order tensor, respectively. For doing clustering or classification of these high order data, it is a conventional way to vectorize these data before hand, as P... | A Report on Multilinear PCA Plus Multilinear LDA to Deal with Tensorial
Data: Visual Classification as An Example | 3,481 |
This manuscript proposes a posterior mean (PM) super-resolution (SR) method with a compound Gaussian Markov random field (MRF) prior. SR is a technique to estimate a spatially high-resolution image from observed multiple low-resolution images. A compound Gaussian MRF model provides a preferable prior for natural images... | Posterior Mean Super-Resolution with a Compound Gaussian Markov Random
Field Prior | 3,482 |
Previous researches have demonstrated that the framework of dictionary learning with sparse coding, in which signals are decomposed as linear combinations of a few atoms of a learned dictionary, is well adept to reconstruction issues. This framework has also been used for discrimination tasks such as image classificati... | Online Discriminative Dictionary Learning for Image Classification Based
on Block-Coordinate Descent Method | 3,483 |
In 3D reconstruction, the recovery of the calibration parameters of the cameras is paramount since it provides metric information about the observed scene, e.g., measures of angles and ratios of distances. Autocalibration enables the estimation of the camera parameters without using a calibration device, but by enforci... | Autocalibration with the Minimum Number of Cameras with Known Pixel
Shape | 3,484 |
A wavelet scattering network computes a translation invariant image representation, which is stable to deformations and preserves high frequency information for classification. It cascades wavelet transform convolutions with non-linear modulus and averaging operators. The first network layer outputs SIFT-type descripto... | Invariant Scattering Convolution Networks | 3,485 |
In this paper, we implement and carry out the comparison of two methods of computer-aided-detection of masses on mammograms. The two algorithms basically consist of 3 steps each: segmentation, binarization and noise suppression using different techniques for each step. A database of 60 images was used to compare the pe... | A comparative evaluation of two algorithms of detection of masses on
mammograms | 3,486 |
This paper introduces a probabilistic graphical model for continuous action recognition with two novel components: substructure transition model and discriminative boundary model. The first component encodes the sparse and global temporal transition prior between action primitives in state-space model to handle the lar... | Substructure and Boundary Modeling for Continuous Action Recognition | 3,487 |
Pedicle screw insertion technique has made revolution in the surgical treatment of spinal fractures and spinal disorders. Although X- ray fluoroscopy based navigation is popular, there is risk of prolonged exposure to X- ray radiation. Systems that have lower radiation risk are generally quite expensive. The position a... | Video Object Tracking and Analysis for Computer Assisted Surgery | 3,488 |
This paper deals with enhancement of images with poor contrast and detection of background. Proposes a frame work which is used to detect the background in images characterized by poor contrast. Image enhancement has been carried out by the two methods based on the Weber's law notion. The first method employs informati... | Enhancement of Images using Morphological Transformation | 3,489 |
We present a rectangle-based segmentation algorithm that sets up a graph and performs a graph cut to separate an object from the background. However, graph-based algorithms distribute the graph's nodes uniformly and equidistantly on the image. Then, a smoothness term is added to force the cut to prefer a particular sha... | Square-Cut: A Segmentation Algorithm on the Basis of a Rectangle Shape | 3,490 |
A method to obtain three-dimensional data of real-world objects by integrating their material properties is presented. The material properties are defined by capturing the Reflectance Fields of the real-world objects. It is shown, unlike conventional reconstruction methods, the method is able to use the reflectance inf... | Integrated three-dimensional reconstruction using reflectance fields | 3,491 |
In real world everything is an object which represents particular classes. Every object can be fully described by its attributes. Any real world dataset contains large number of attributes and objects. Classifiers give poor performance when these huge datasets are given as input to it for proper classification. So from... | Single Reduct Generation Based on Relative Indiscernibility of Rough Set
Theory | 3,492 |
Marker-based motion capture (MoCap) systems can be composed by several dozens of cameras with the purpose of reconstructing the trajectories of hundreds of targets. With a large amount of cameras it becomes interesting to determine the optimal reconstruction strategy. For such aim it is of fundamental importance to und... | Reconstruction error in a motion capture system | 3,493 |
This paper proposes a novel adaptive algorithm to extract facial feature points automatically such as eyebrows corners, eyes corners, nostrils, nose tip, and mouth corners in frontal view faces, which is based on cumulative histogram approach by varying different threshold values. At first, the method adopts the Viola-... | Extraction of Facial Feature Points Using Cumulative Histogram | 3,494 |
In this paper we propose a graph-based data clustering algorithm which is based on exact clustering of a minimum spanning tree in terms of a minimum isoperimetry criteria. We show that our basic clustering algorithm runs in $O(n \log n)$ and with post-processing in $O(n^2)$ (worst case) time where $n$ is the size of th... | Clustering Using Isoperimetric Number of Trees | 3,495 |
This paper presents a novel Coprime Blurred Pair (CBP) model for visual data-hiding for security in camera surveillance. While most previous approaches have focused on completely encrypting the video stream, we introduce a spatial encryption scheme by blurring the image/video contents to create a CBP. Our goal is to ob... | A Co-Prime Blur Scheme for Data Security in Video Surveillance | 3,496 |
Research is taking place to find effective algorithms for content-based image representation and description. There is a substantial amount of algorithms available that use visual features (color, shape, texture). Shape feature has attracted much attention from researchers that there are many shape representation and d... | Kernel Density Feature Points Estimator for Content-Based Image
Retrieval | 3,497 |
In depth from defocus (DFD), when images are captured with different camera parameters, a relative magnification is induced between them. Image warping is a simpler solution to account for magnification than seemingly more accurate optical approaches. This work is an investigation into the effects of magnification on t... | Analysis of Magnification in Depth from Defocus | 3,498 |
The automatic recognition of facial expressions has been an active research topic since the early nineties. There have been several advances in the past few years in terms of face detection and tracking, feature extraction mechanisms and the techniques used for expression classification. This paper surveys some of the ... | Face Expression Recognition and Analysis: The State of the Art | 3,499 |
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