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第三届全国智能视觉监控学术会议

作者： Qi Dong Guangping Xu Liu Jing Yanbing Xue Hua Zhang Key Laboratory of Intelligence Computing and New Software Technology TianjinChina300384 Key Laboratory of Computer Vision and SystemMinistry of EducationTianjinChina300384 School of Computer and CommunicationTianjin University of TechnologyTianjinChina300384

ISBN: (纸本)9781457718342

The contour analysis and identification are the important aspects in visual surveillance *** paper proposes a fuzzy identification method of ***,according to the description of a contour based on the chain-code method,the proposed method utilizes the statistical features of contours including the chain-code entropy and chain-code space distribution entropies,from which the feature vector of a contour is ***,the method generates the contour pattern from some contour samples and uses the approaching principle to identify a *** our method integrates effectively multiple statistical feathers of its chain-code and employs a fuzzy pattern recognition technique,the experiments show quantitatively that it can achieve good results from various metrics.

关键词： Image Contour Fuzzy pattern Chain Code Object recognition

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Low resolution facial image recognition via multiple kernel criterion

Low resolution facial image recognition via multiple kernel ...

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Asian Conference on pattern recognition (ACPR)

作者： Chuan-Xian Ren Dao-Qing Dai Hong Yan Center of Computer Vision and Department of Mathematics Sun Yat-Sen University Guangzhou China Department of Electric Engineering City University of Hong Kong Hong Kong China

Practical face recognition systems are sometimes confronted with low-resolution (LR) images. Most existing feature extraction algorithms aim to preserve relational structure among objects of the input space in a linear embedding space. However, it has been a consensus that such complex visual learning tasks will be well be solved by adopting multiple descriptors to more precisely characterize the data for improving performance. In this paper, we addresses the problem of matching LR and high-resolution images that are difficult for conventional methods in practice due to the lack of an efficient similarity measure, and a multiple kernel criterion (MKC) is proposed for LR face recognition without any super-resolution (SR) preprocessing. Different image descriptors including RsL2, LBP, Gradientface and IMED are considered as the multiple kernel generators and the Gaussian function is exploited as the distance induced kernel. MKC solves this problem by minimizing the inconsistency between the similarities captured by the multiple kernels, and the nonlinear objective function can be alternatively minimized by a constrained eigenvalue decomposition. Experiments on benchmark databases show that our MKC method indeed improves the recognition performance.

关键词： Kernel Image resolution Face recognition Face Feature extraction Databases Optimization

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A novel approach for delineation and feature extraction in QRS complex of ECG signal

A novel approach for delineation and feature extraction in Q...

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International Conference on Image Information Processing

作者： Sayak Pramanik Rupendra Nath Mitra Sucharita Mitra Bidyut Baran Chaudhuri Department of Electronics & Communication Institute of Engineering and Management Kolkata India Department of Electronics Netaji Nagar Day College Kolkata India Network Planning & Optimization Nokia Siemens Networks Private Limited Kolkata India Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India

This paper reports the development of a software suite to be accessed in future with any General Packet Radio Service (GPRS) enabled mobile phone or Personal Digital Assistant (PDA) for the extraction and analysis of disease-related features from the images of paper based ECG records. In India and other developing countries, the cheaper paper based ECG machines are mainly used. Also in rural areas of these countries - where there is acute dearth of qualified cardiologists, the cardiac diseases are still the major silent killers. One way of addressing this problem is cellular medicine which necessitates an intelligent cardiac parameter extraction algorithm. In our bid to address exactly this requirement, a software is developed with the help of few image processing techniques. At first, the background noises i.e. the gridlines are removed by thresholding technique. Binarization and thinning has been done for extraction of digital time data and then Discrete Wavelet Transform (DWT) and water reservoir based pattern recognition technique are subsequently used to delineate other important ECG parameters for ECG interpretation.

关键词： Electrocardiography Feature extraction pattern recognition Information processing Reservoirs Strips

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A Painting Based Technique for Skew Estimation of Scanned Documents

A Painting Based Technique for Skew Estimation of Scanned Do...

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International Conference on Document Analysis and recognition

作者： Alireza Alaei Umapada Pal P. Nagabhushan Fumitaka Kimura Department of Studies in Computer Science University of Mysore Mysore India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Graduate School of Engineering Mie University Japan

In this paper, we propose an efficient skew estimation technique based on Piece-wise Painting Algorithm (PPA) for scanned documents. Here we, at first, employ the PPA on the document image horizontally and vertically. Applying the PPA on both the directions, two painted images (one for horizontally painted and other for vertically painted) are obtained. Next, based on statistical analysis some regions with specific height (width) from horizontally (vertically) painted images are selected and top (left), middle (middle) and bottom (right) points of such selected regions are categorized in 6 separate lists. Utilizing linear regression, a few lines are drawn using the lists of points. A new majority voting approach is also proposed to find the best-fit line amongst all the lines. The skew angle of the document image is estimated from the slope of the best-fit line. The proposed technique was tested extensively on a dataset containing various categories of documents. Experimental results showed that the proposed technique achieved more accurate results than the state-of-the-art methodologies.

关键词： Estimation Painting Fitting Linear regression Text analysis Writing

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Dynamic modeling of streaklines for motion pattern analysis in video

Dynamic modeling of streaklines for motion pattern analysis ...

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IEEE computer Society Conference on computer vision and pattern recognition Workshops (CVPRW)

作者： Nandita M. Nayak Bi Song Amit K. Roy-Chowdhury

Natural videos consist of multiple objects interacting with each other in complex ways. Analysis of such videos is a very challenging problem. The underlying patterns of motion contain valuable information about the activities and hence, it is necessary to devise efficient mechanisms for extraction and analysis of these patterns. Tracking is often infeasible in these scenarios. Recently, flow-based modeling methods based on the concept of streaklines in fluid mechanics have been proposed to deal with videos of crowds. In this paper, we show how the streaklines representation can be combined with dynamical systems modeling approaches in order to analyze the motion patterns in a wide range of natural videos. This combination provides a powerful tool to identify similar segments in a video that exhibit similar motion patterns. We show results on challenging datasets by demonstrating unsupervised clustering of similar motion patterns (which often represent similar activity patterns) and detection of changes in the video.

关键词： Computational modeling Motion segmentation Hidden Markov models Optical imaging Nonlinear optics Tracking Change detection algorithms

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Semantic image segmentation using oriented pattern analysis

Semantic image segmentation using oriented pattern analysis

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International Conference on Information, Communications and Signal Processing

作者： Hui Ting Ong Kai-Kuang Ma School of Electrical and Electronic Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781457700293

Semantic image segmentation is often served as an instrumental front-end preprocessing of many image processing and computer vision applications. Different from the existing semantic segmentation methods which mostly rely on database training, a simple and effective approach is proposed in this paper by employing the oriented pattern as a class-discriminative feature, besides the use of color and texture. The developed algorithm is to discriminate three specific semantic classes - sky, foliage, and building, which are commonly encountered in typical color images containing outdoor scene. In our approach, two maps will be generated from the input image: 1) the over-segmented map by using JSEG, and 2) the oriented pattern map by measuring the orientation coherence at each pixel position. Based on these maps, the region coherence of each over-segmented patch can be obtained by taking the average of all the orientation coherence values within the patch. The semantic class labeling for the patch can be simply conducted by checking the computed region coherence value against two empirically determined thresholds. Extensive simulation experiments have been conducted by testing various color images acquired from various sources, including the Microsoft Research Cambridge (MSRC) Object recognition Image Database that contains manually-segmented regions as the ground truth. All experimental results clearly show that the proposed method is able to consistently deliver highly attractive performance.

关键词： Semantics Image segmentation Coherence Buildings Vectors Image color analysis computer vision

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Rapid reconstruction of small objects on mobile phones

Rapid reconstruction of small objects on mobile phones

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IEEE computer Society Conference on computer vision and pattern recognition Workshops (CVPRW)

作者： Andreas Hartl Lukas Gruber Clemens Arth Stefan Hauswiesner Dieter Schmalstieg Institute of Computer Graphics and Vision Graz Technical University Austria

Augmented Reality (AR) on mobile phones is receiving more and more attention recently, becoming a popular research topic and an important commercial field. In this paper we present a lightweight method to create coarse 3D models of small-scale objects. The goal is to give the users the possibility to create and maintain AR content themselves without the need for expensive tools and complex interaction. Our algorithm is based on shape-from-silhouette using voxel carving and runs on modern smartphone hardware. 3D models of certain object groups can be generated interactively and instantly. The actual result is visualized continuously using image based rendering methods to inform the user about the actual model quality. Given a suitably accurate model it can further be used for any means of AR and can easily be shared with other users. The usability of our approach is evaluated using modern smartphone hardware (see Figure 1). The advantages are demonstrated using a set of models for playing a board game.

关键词： Solid modeling Computational modeling Three dimensional displays Visualization Hardware Image color analysis Rendering (computer graphics)

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An analysis on the two-phase test sample sparse representation method and an improved method

An analysis on the two-phase test sample sparse representati...

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2011 International conference on Instrumentation,Measurement,computer,Communication and Control (IMCCC2011)(第一届仪器测量、计算机通信与控制国际会议)

作者： Yuwu Lu Dept. of Mathematics of science school Inner Mongol University of TechnologyHohhotInner MongoliaChina

The recently proposed two-phase test sample sparse representation (TPTSR) method makes a great contribution to the field of face *** TPTSR uses a computationally very efficient algorithm,it can obtain a better performance than the well-known sparse representation *** the first phase of TPTSR,the determined M nearest neighbors for the test sample seem not to be optimal in terms of the representation *** other words,it is probably that there exist M training samples whose linear combination has a smaller deviation from the test *** deviation is referred to as representation error of the test *** the smaller the representation error,the higher the accuracy,then it will be possible that one can obtain a better face recognition *** this paper,in order to explore this issue,we propose an improved *** method revises the first phase of TPTSR as a step that uses the global search algorithm to determine the M " optimal " nearest neighbors of the test *** show the representation error and classification accuracy of the improved method and TPTSR by experimental results.

关键词： Face recognition pattern recognition sparse representation transform methods computer vision

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IEEE computer Society Conference on computer vision and pattern recognition Workshops (CVPRW)

作者： Atousa Torabi Guillaume-Alexandre Bilodeau LITIV Laboratory Department of computer engineering and software engineering École Polytechnique de Montréal Montreal QUE Canada

The robustness of Mutual Information (MI), the most used multimodal dense stereo correspondence measure, is restricted by the size of the matching windows. However, obtaining the appropriately sized MI windows for matching thermal-visible pair of images of multiple people with various poses, clothes, distances to cameras, and different levels of occlusions is quite challenging. In this paper, we propose local self-similarity (LSS) as a multimodal dense stereo correspondence measure. We integrated LSS as a similarity metric with a disparity voting registration method to demonstrate the suitability of LSS for a visible-thermal stereo registration method. We have analyzed comparatively LSS and MI as multimodal correspondence measures and discussed LSS advantages compared to MI. We have also tested our LSS-based registration method in several indoor videos of multiple people and shown that our registration method outperforms the most recent MI-based registration method in the state-of-the-art.

关键词： Bismuth pattern matching Joints Robustness Cameras Humans Layout

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心理认知计算的研究现状及发展趋势

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模式识别与人工智能 2011年第2期24卷 215-225页

作者：王志良郑思仪王先梅王巍北京科技大学信息工程学院北京100083 武警北京指挥学院北京100012

心理认知计算是智能化人机交互技术的一个重要组成部分,近年来得到广泛的关注.文中综述国内外心理认知计算的研究进展.首先介绍心理认知计算的相关概念,详细叙述心理状态理解的研究内容和机制.其次总结心理认知的神经生物学研究成果,对... 详细信息

心理认知计算是智能化人机交互技术的一个重要组成部分,近年来得到广泛的关注.文中综述国内外心理认知计算的研究进展.首先介绍心理认知计算的相关概念,详细叙述心理状态理解的研究内容和机制.其次总结心理认知的神经生物学研究成果,对心理情感状态和心理认知状态的研究现状进行了比较,从模式提取和模型建立两方面对心理认知在人机交互中的发展趋势作了分析,提出多模态信息融合的多层级心理状态视觉认知计算模型框架.最后讨论研究心理认知计算的重要意义和当前存在的主要困难.

关键词：心理状态理解认知计算视觉人机交互

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