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A Graph Reduction Method for 2D Snake Problems

A Graph Reduction Method for 2D Snake Problems

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Conference on computer vision and pattern recognition (CVPR)

作者： Jianhua Yan Keqi Zhang Chengcui Zhang Shu-Ching Chen Giri Narasimhan School of Computing and Information Sciences Florida International University USA Department of Environmental Studies & International Hurricane Research Center Florida State University USA Department of Computer and Information Sciences University of Alabama Birmingham USA

Energy-minimizing active contour models (snakes) have been proposed for solving many computer vision problems such as object segmentation, surface reconstruction, and object tracking. Dynamic programming which allows natural enforcement of constraints is an effective method for computing the global minima of energy functions. However, this method is only limited to snake problems with one dimensional (ID) topology (i.e., a contour) and cannot handle problems with two-dimensional (2D) topology. In this paper, we have extended the dynamic programming method to address the snake problems with 2D topology using a novel graph reduction algorithm. Given a 2D snake with first order energy terms, a set of reduction operations are defined and used to simplify the graph of the 2D snake into one single vertex while retaining the minimal energy of the snake. The proposed algorithm has a polynomial-time complexity bound and the optimality of the solution for a reducible 2D snake is guaranteed. However, not all types of 2D snakes can be reduced into one single vertex using the proposed algorithm. The reduction of general planar snakes is an NP-complete problem. The proposed method has been applied to optimize 2D building topology extracted from airborne LIDAR data to examine the effectiveness of the algorithm. The results demonstrate that the proposed approach successfully found the global optima for over 98% of building topology in a polynomial time.

关键词： Topology Dynamic programming Polynomials Active contours computer vision Object segmentation Surface reconstruction NP-complete problem Optimization methods Data mining

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Segmenting Motions of Different Types by Unsupervised Manifold Clustering

Segmenting Motions of Different Types by Unsupervised Manifo...

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Conference on computer vision and pattern recognition (CVPR)

作者： Alvina Goh Rene Vidal Center for Imaging Science Johns Hopkins University Baltimore MD USA

We propose a novel algorithm for segmenting multiple motions of different types from point correspondences in multiple affine or perspective views. Since point trajectories associated with different motions live in different manifolds, traditional approaches deal with only one manifold type: linear subspaces for affine views, and homographic, bilinear and trilinear varieties for two and three perspective views. As real motion sequences contain motions of different types, we cast motion segmentation as a problem of clustering manifolds of different types. Rather than explicitly modeling each manifold as a linear, bilinear or multilinear variety, we use nonlinear dimensionality reduction to learn a low-dimensional representation of the union of all manifolds. We show that for a union of separated manifolds, the LLE algorithm computes a matrix whose null space contains vectors giving the segmentation of the data. An analysis of the variance of these vectors allows us to distinguish them from other vectors in the null space. This leads to a new algorithm for clustering both linear and nonlinear manifolds. Although this algorithm is theoretically designed for separated manifolds, our experiments demonstrate its performance on real data where this assumption does not hold. We test our algorithm on the Hopkins 155 motion segmentation database and achieve an average classification error of 4.8%, which compares favorably against state-of-the art multiframe motion segmentation methods.

关键词： Clustering algorithms Motion segmentation computer vision Vectors Null space Analysis of variance Data analysis Functional analysis Algorithm design and analysis Testing

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The Hierarchical Isometric Self-Organizing Map for Manifold Representation

The Hierarchical Isometric Self-Organizing Map for Manifold ...

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Haiying Guan Matthew Turk Computer Science Department University of California Santa Barbara CA USA

We present an algorithm, Hierarchical ISOmetric Self-Organizing Map (H-ISOSOM), for a concise, organized manifold representation of complex, non-linear, large scale, high-dimensional input data in a low dimensional space. The main contribution of our algorithm is threefold. First, we modify the previous ISOSOM algorithm by a local linear interpolation (LLl) technique, which maps the data samples from low dimensional space back to high dimensional space and makes the complete mapping pseudo-invertible. The modified-ISOSOM (M-ISOSOM) follows the global geometric structure of the data, and also preserves local geometric relations to reduce the nonlinear mapping distortion and make the learning more accurate. Second, we propose the H-ISOSOM algorithm for the computational complexity problem of Isomap, SOM and LLI and the nonlinear complexity problem of the highly twisted manifold. H-ISOSOM learns an organized structure of a non-convex, large scale manifold and represents it by a set of hierarchical organized maps. The hierarchical structure follows a coarse-to-fine strategy. According to the coarse global structure, it "unfolds " the manifold at the coarse level and decomposes the sample data into small patches, then iteratively learns the nonlinearity of each patch in finer levels. The algorithm simultaneously reorganizes and clusters the data samples in a low dimensional space to obtain the concise representation. Third, we give quantitative comparisons of the proposed method with similar methods on standard data sets. Finally, we apply H-ISOSOM to the problem of appearance-based hand pose estimation. Encouraging experimental results validate the effectiveness and efficiency of H-ISOSOM.

关键词： Nonlinear distortion Clustering algorithms Large-scale systems Independent component analysis Computational complexity Iterative algorithms Humans computer vision Principal component analysis Kernel

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Efficient Image Processing with the Apply Language

Efficient Image Processing with the Apply Language

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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Leonard G. C. Hamey Macquarie University Sydney Australia

ISBN: (纸本)9781424431618

Apply is a Domain-Specific Language for image processing and low-level computer vision. Apply allows programmers to write kernel operations that focus on the computation for a single pixel location. The compiler generates code to perform the kernel computation over entire images. The original Apply implementation was developed 20 years ago for efficient processing on parallel architectures. The current-generation Apply compiler targets efficient code generation for general-purpose computers, typically outperforming handwritten code, while maintaining the simplicity of the original language. The use of modern compiler writing tools, specifically Stratego/XT, has facilitated improvements in the language design and made it easy to target the compiler to different environments. A large number of computer vision and image processing operations can be expressed in Apply. However, some algorithms require additional features. To motivate future language development, we analyse the requirements of the algorithms provided in a commercial machine vision library.

关键词： Image processing computer vision Kernel Domain specific languages Programming profession Parallel architectures Writing Algorithm design and analysis Machine vision Libraries

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Ruttier Obstacle Classification by use of Fractional B-spline Wavelets and Moments

Ruttier Obstacle Classification by use of Fractional B-splin...

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Eurocon

作者： Anca Discant Simina Emerich Eugen Lupu Alexandrina Rogozan Abdelaziz Bensrhair Basis of Electronics Department Technical University of Cluj Napoca Cluj-Napoca Romania Communications Department Technical University of Cluj Napoca Cluj-Napoca Romania Department of Computer Science and Information Engineering National Institute for Applied Sciences Rouen France

Applications of wavelet analysis are widespread and cover many fields of scientific research including image processing, classification and recognition. In addition, the mathematical concept of moments has been used for many years in pattern recognition and image processing. We present a new discovered family of splines, named fractional B-splines which we used as mother wavelet functions. The resulted fractional B-spline wavelets constitute a part of the features vector used in our ruttier obstacle classification system. We compared different recognition rates obtained by the use of different mother wavelet functions, but in order to improve the recognition rates, we added first order statistics features and the seven moments of Hu. The artificial vision systems was developed having as model the human system, and therefore the objects recognition task is reduced to a classification using features extracted from images. In our case, the features vector is formed by wavelet transform of fractional B-splines and seven statistics features, followed by the seven moments of Hu.

关键词： Spline Image recognition Image processing Statistics Wavelet analysis Image analysis pattern recognition Machine vision Humans Object recognition

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An Incremental On-line Parsing Algorithm for Recognizing Sketching Diagrams

An Incremental On-line Parsing Algorithm for Recognizing Ske...

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International Conference on Document Analysis and recognition

作者： J. Mas G. Sanchez J. Llados B. Lamiroy Computer Vision Center Department Ciències de la Computació Edifici O Universidad Autonoma de Barcelona Bellaterra Spain Ecole des Mines INPL and LORIA Nancy France

This paper presents a syntactic recognition approach for on-line drawn graphical symbols. The proposed method consists in an incremental on-line predictive parser based on symbol descriptions by an adjacency grammar. The parser analyzes input strokes as they are drawn by the user and is able to get ahead which symbols are likely to be recognized when a partial subshape is drawn in an intermediate state. In addition, the parser takes into account two issues. First, symbol strokes are drawn in any order by the user and second, since it is an on-line framework, the system requires real-time response. The method has been applied to an on-line sketching interface for architectural symbols.

关键词： Shape Text analysis Image recognition Graphics pattern recognition computer vision Real time systems Human computer interaction Heart Image analysis

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A Two Stage recognition Scheme for Handwritten Tamil Characters

A Two Stage Recognition Scheme for Handwritten Tamil Charact...

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International Conference on Document Analysis and recognition

作者： U. Bhattacharya S.K. Ghosh S. Parui Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

India is a multilingual multiscript country with more than 18 languages and 10 different major scripts. Not enough research work towards recognition of handwritten characters of these Indian scripts has been done. Tamil, an official as well as popular script of the southern part of India, Singapore, Malaysia, and Sri Lanka has a large character set which includes many compound characters. Only a few works towards handwriting recognition of this large character set has been reported in the literature. Recently, HP Labs India developed a database of handwritten Tamil characters. In the present paper, we describe an off-line recognition approach based on this database. The proposed method consists of two stages. In the first stage, we apply an unsupervised clustering method to create a smaller number of groups of handwritten Tamil character classes. In the second stage, we consider a supervised classification technique in each of these smaller groups for final recognition. The features considered in the two stages are different. The proposed two-stage recognition scheme provided acceptable classification accuracies on both the training and test sets of the present database.

关键词： Character recognition Handwriting recognition Spatial databases pattern recognition Testing Speech recognition computer vision Natural languages Clustering methods Personal communication networks

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Preliminary level cardiac abnormality detection using wireless telecardiology system 1

Preliminary level cardiac abnormality detection using wirele...

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1st International Conference on the Digital Society, ICDS 2007

作者： Mitra, M. Mitra, S. Bera, J.N. Gupta, R. Chaudhuri, B.B. Dept. of Applied Physics University of Calcutta India Computer Vision and Pattern Recognition Unit ISI Kolkata India

ISBN: (纸本)0769527604

This paper describes a portable diagnostic telecardiology system, aimed to benefit the rural people of a third world country like India. The designed system consists of two major blocks;the first one is required to be carried to the patient home, named ¿Portable Telecardiology Kit¿. The second one, named ¿Automated Cardiac Signal Processor¿, a PC based system, to be permanently placed at the nearest rural health care center. The ¿Portable Telecardiology Kit¿ contains a portable ECG machine, a dedicated microcontroller-based full duplex communication system, both interfaced, in a single enclosure. This kit will convert the ECG signal along with a tag page (containing different information regarding patient¿s health and history of illness) to a digitized serial electromagnetic wave. The signal may be transmitted over a distance of about 7-10 km through a cordless phone under full duplex mode. The PC-based system, after receiving the transmitted signal from patient site, extract the ECG signal after proper filtering, and then pass the signal through an in-built knowledge-base. Finally, a rule-based rough set decision system is generated for the development of an inference engine for disease identification from these time-plane features. The system will generate a report indicating the preliminary level abnormalities, and the precautions that can be adopted at an early stage. The entire report is then sent to the Portable kit at the patient bed-site. © 2007 IEEE.

关键词： Electrocardiograms

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A method for multiple morph targets tracking based on region growing

A method for multiple morph targets tracking based on region...

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International Conference on Wavelet Analysis and pattern recognition (ICWAPR)

作者： Heng-Xin Chen Bin Fang Yuan-Yan Tang College of Computer Science Chongqing University Chongqing China

It is very important to count passengers who get on and get off for scheduling bus effectively. The tracking methods based on target shape and feature points can not be adopted to this case, because the target shapes keep changing from time to time randomly and even appear partially in field of vision captured. Based on difference image and region growing, a new method is proposed in this paper for tracking the multiple moving targets whose shapes are variable. The result of experiment shows that the method is able to count passengers with preferable accuracy in real-time application.

关键词： Target tracking Shape Cameras Wavelet analysis pattern analysis pattern recognition Object detection Streaming media Color

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Off-Line Handwritten Character recognition of Devnagari Script

Off-Line Handwritten Character Recognition of Devnagari Scri...

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International Conference on Document Analysis and recognition

作者： U. Pal N. Sharma T. Wakabayashi F. Kimura Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Graduate School of Engineering Mie University Tsu Japan

In this paper we present a system towards the recognition of off-line handwritten characters of Devnagari, the most popular script in India. The features used for recognition purpose are mainly based on directional information obtained from the arc tangent of the gradient. To get the feature, at first, a 2times2 mean filtering is applied 4 times on the gray level image and a non-linear size normalization is done on the image. The normalized image is then segmented to 49times49 blocks and a Roberts filter is applied to obtain gradient image. Next, the arc tangent of the gradient (direction of gradient) is initially quantized into 32 directions and the strength of the gradient is accumulated with each of the quantized direction. Finally, the blocks and the directions are down sampled using Gaussian filter to get 392 dimensional feature vector. A modified quadratic classifier is applied on these features for recognition. We used 36172 handwritten data for testing our system and obtained 94.24% accuracy using 5-fold cross-validation scheme.

关键词： Character recognition Handwriting recognition Filters Filtering pattern recognition Image segmentation Automation computer vision System testing Natural languages

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