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检索条件"任意字段=Proceedings of the Thirteenth Indian Conference on Computer Vision, Graphics and Image Processing"

共 1469 条记录，以下是1311-1320 订阅

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A Novel Learning-Based Framework for Detecting Interesting Events in Soccer Videos

A Novel Learning-Based Framework for Detecting Interesting E...

引用

indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Nisha Jain Santanu Chaudhury Sumantra Dutta Roy Prasenjit Mukherjee Krishanu Seal Kumar Talluri Electrical Engineering Department IIT Delhi USA AOL

We present a novel learning-based framework for detecting interesting events in soccer videos. The input to the system is a raw soccer video. We have learning at three levels-learning to detect interesting low-level features from image and video data using support vector machines (hereafter, SVMs), and a hierarchical conditional random field- (hereafter, CRF-) based methodology to learn the dependencies of mid-level features and their relation with the low level features, and high level decisions (dasiainteresting eventspsila) and their relation with the mid-level features: all on the basis of training video data. Descriptors are spatio-temporal in nature - they can be associated with a region in an image or a set of frames. Temporal patterns of descriptors characterise an event. We apply this framework to parse soccer videos into Interesting (a goal or a goal miss) and Non-Interesting videos. We present results of numerous experiments in support of the proposed strategy.

关键词： Event detection Videos computer vision Hidden Markov models Machine learning image analysis Unsupervised learning computer graphics image processing Support vector machines

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Texture Classification Using Three Circular Filters

Texture Classification Using Three Circular Filters

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Shripad Kondra Vincent Torre S.I.S.S.A. Trieste Italy

A new method for texture classification is presented. The proposed method uses only 3 circular filters. images are first filtered using these filters, then thresholded and averaged over two small neighborhoods. Universal textons are generated without learning from the training sets. 80 universal textons are used for each neighborhood. The feature space is reduced in one neighborhood by grouping into 4 bins. Each image is thus represented by a 2D histogram giving a 320 (80 times 4) dimensional feature vector (Model). Models are then trained with Support Vector Machines using chi2 kernel. The results are compared with state of art texture classification methods on 4 texture databases. The proposed method performs better than all previously proposed techniques on the KTH-TIPS database, despite using only 3 circular filters.

关键词： Filter bank Histograms Kernel Support vector machines Support vector machine classification Spatial databases Visual databases image segmentation computer vision computer graphics

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Improving image Decomposition Method of the 3-MRC Coding of Scanned Compound Document images

Improving Image Decomposition Method of the 3-MRC Coding of ...

引用

indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Gopal Lakhani Texas Tech University Lubbock TX USA

This paper discusses image decomposition problem of the 3-layer MRC model based coding of scanned (noisy) document images. A widely-used approach for document decomposition is to divide the document image into blocks and split the pixel histogram of each block into two halves by minimizing the sum of variance of its pixels with the mean of the halves. We propose to split a block by minimizing the variance of one half with its minimum pixel and the variance of the other half with its maximum pixel. Our goal is to increase the gap between the two halves by avoiding splitting of any cluster of pixels into both halves. It should help reduce complexity of the generated mask. Moreover, we do not decompose a block if it has no edge points, again to reduce the mask complexity. We also implement a noise reduction heuristic in the mask layer to correct placement of transition pixels. We provide simple analysis and evaluate block energy in terms of the DCT coefficients of the resulting FG/BG layer blocks. Experimental results show that code size of the mask layer of our test images, obtained using proposed processing is reduced to nearly half of the mask obtained by a straight-forward 3-MRC implementation.

关键词： image decomposition image coding Pixel Noise reduction image reconstruction Entropy computer vision computer graphics image processing Histograms

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An Algebraic Framework for Discrete Basis Functions in computer vision

An Algebraic Framework for Discrete Basis Functions in Compu...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Paul O'Leary Matther Harker Institute for Automation University of Leoben Leoben Austria

This paper presents a fundamentally new algebraic approach to the analysis and synthesis of discrete orthogonal basis functions. It provides the theoretical background to unify Fourier, Gabor and discrete orthogonal polynomial moments. For the first time, a set of objective tests are proposed to measure the quality of basis functions. It consists of two main sections: the theoretical background on the generation and orthogonalization of basis functions together with a new solution for the computation of spectra from incomplete data, as well as the implementation of interpolation for all orthogonal basis functions; a new approach to discrete orthogonal polynomials, proving that there is one and only one unitary discrete polynomial basis. Furthermore, the concept of anisotropic moments is introduced and applied to 2D seismic data, which is an image processing problem. The new polynomial basis is numerically better conditioned than the discrete cosine transform. This opens the door to new image compression algorithms, offering a higher compression ratio than the well known JPEG method, for the same numerical effort.

关键词： computer vision Polynomials image coding Testing Time measurement Interpolation Anisotropic magnetoresistance image processing Discrete cosine transforms Transform coding

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Fragment Based Tracking for Scale and Orientation Adaptation

Fragment Based Tracking for Scale and Orientation Adaptation

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Viswanathan Srikrishnan Tadinada Nagaraj Subhasis Chaudhuri Electrical Engineering Department V.I.P Laboratory Indian Institute of Technology Bombay Mumbai India

In this work, we propose a simple yet highly effective algorithm for tracking a target through significant scale and orientation change. We divide the target into a number of fragments and tracking of the whole target is achieved by coordinated tracking of the individual fragments. We use the mean shift algorithm to move the individual fragments to the nearest minima, though any other method like integral histograms could also be used. In contrast to the other fragment based approaches, which fix the relative positions of fragments within the target, we permit the fragments to move freely within certain bounds. Furthermore, we use a constant velocity Kalman filter for two purposes. Firstly, Kalman filter achieves robust tracking because of usage of a motion model. Secondly, to maintain coherence amongst the fragments, we use a coupled state transition model for the Kalman filter. Using the proposed tracking algorithm, we have experimented on several videos consisting of several hundred frames length each and obtained excellent results.

关键词： Target tracking Histograms Videos computer vision Robustness Shape computer graphics image processing Coherence Taxonomy

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Robust Watermarking Scheme Based on Multiresolution Fractional Fourier Transform

Robust Watermarking Scheme Based on Multiresolution Fraction...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Gaurav Bhatnagar Balasubramanian Raman Department of Mathematics Indian Institute of Technology Roorkee Roorkee India

In this paper, a new robust watermarking scheme is proposed in multiresolution fractional Fourier transform domain using singular value decomposition. The watermark is embedded in the high frequency sub-band of the host image at coarsest level. Although the schemes based on SVD are robust but fail under ambiguity attacks. In this attack, both the owner and attacker can extract their watermark from the watermarked image. To prevent ambiguity, the normalized mass matrix is formed and embedded in the host image. In extraction, normalized mass matrix is extracted first and compared with original one. If the similarity is found then the singular values are extracted to construct the watermark. Experimental evaluation demonstrates that the proposed scheme is able to withstand a variety of attacks.

关键词： Robustness Watermarking Fourier transforms Spatial resolution Frequency domain analysis Discrete transforms Signal resolution Time frequency analysis image resolution Mathematics

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Anisotropic Diffusion and Segmentation of Colored Flowers

Anisotropic Diffusion and Segmentation of Colored Flowers

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Shoma Chatterjee Department of Computer Science and Engineering Jaypee Institute of Information Technology Noida Uttar Pradesh India

This paper presents a new anisotropic diffusion method for multi-valued images. The colored flowers are segmented from the background. In my diffusion technique the edge stopping function is computed as inversely proportional to the weighted sum of gradients of color components. The value of edge stopping function tends to zero as the weighted sum of three color gradients becomes large. The other algorithm further explores an existing diffusion technique based on structure tensors. The multivalued image diffuses using a system of coupled differential equations in the direction of minimal change. The paper presents the results of anisotropic diffusion and segmentation of colored flowers. The new method can also be applied for anisotropic diffusion of other multivalued images.

关键词： Anisotropic magnetoresistance image segmentation computer science Smoothing methods Tensile stress image edge detection Color Information technology Differential equations Robustness

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Design and Implementation of a Robust Palm Biometrics Recognition and Verification System

Design and Implementation of a Robust Palm Biometrics Recogn...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Saurabh Parashar Anand Vardhan C. Patvardhan Prem Kumar Kalra Dayalbagh Educational Institute (Deemed University) Agra India Indian Institute of Technology New Delhi India

Complete design and implementation of a robust palm biometrics recognition and verification system has been presented. The paper attempts to scientifically develop a comprehensive set of hand geometry features and develop an original algorithm from a fundamental level to robustly compute a selected set of features so as to minimize palm placement effect. These features are combined with chrominance features, to achieve recognition and verification accuracy, significant with respect to the current state in palm biometrics research. The algorithm has been kept robust, simple and computationally efficient while the implementation is relatively inexpensive. The experiments on recognition, Principal Components Analysis (PCA) and verification, on a dataset of 100 users strongly confirm the utility of robustly calculating a comprehensive set of scientifically selected hand geometry features. The results uncover the potential of hand geometry features and confirm that the system can be used in medium to high security environments.

关键词： Robustness Biometrics Geometry Principal component analysis image recognition Fingerprint recognition Geometrical optics image databases computer vision computer graphics

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Automatic Perspective Camera Calibration Based on an Incomplete Set of Chessboard Markers

Automatic Perspective Camera Calibration Based on an Incompl...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Alessandro Bevilacqua Alessandro Gherardi Ludovico Carozza ARCES University of Bologna Bologna Italy

The measurement in metric units from a perspective view of a real world object is an important task in many computer vision applications. The goal of the perspective calibration is to map the reference coordinates of the 3D object into the 2D image coordinates. This is usually done by recovering the perspective transformation parameters by presenting to the camera a view of a known calibration pattern. Many of the available algorithms require to process all the points of the calibration pattern in order to recover the transformation parameters effectively. The approach we present for the computation of the inverse perspective transformation does not require to consider all the grid points. Rather, a grid matching between the 3D points projection and the model is performed exploiting a graph based approach. Extensive experiments have proved the efficacy of the algorithm in different application fields such as camera calibration and automotive headlight beam characterization.

关键词： Cameras Calibration Layout Pattern matching Robot kinematics Navigation computer vision Automotive engineering Robotics and automation Optical computing

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Animation Geometry Compression Using the Linear Discriminant Analysis

Animation Geometry Compression Using the Linear Discriminant...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： A.R. Vamsidhar P.K. Bora Sanjib Das Department of Electronics and Communication Engineering Indian Institute of Technology Guwahati Guwahati India

We propose a new method to compress the geometry component of 3D animation sequence. It is based on the linear discriminant analysis (LDA) of the animation geometry data. The redundancy across the animation frames has been exploited by using the LDA in the temporal direction. Owing to the redundancy between the frames of a class, the covariance matrix of that class for the LDA computation may become singular. To overcome this drawback, we first transform the data into a new basis using the principal component analysis (PCA) and then apply the LDA on a few principal components. The reconstruction is simple and involves two stages: firstly for the LDA and then for the PCA. The experimental results show that the proposed method has the advantage of better reconstruction error at high compression ratios.

关键词： Animation Geometry Linear discriminant analysis Principal component analysis image coding image reconstruction Surface texture Rough surfaces Surface roughness Redundancy

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