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检索条件"任意字段=MIPPR 2007: Pattern Recognition and Computer Vision"

共 1016 条记录，以下是411-420 订阅

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Trajectory series analysis based event rule induction for visual surveillance

Trajectory series analysis based event rule induction for vi...

引用

2007 IEEE computer Society Conference on computer vision and pattern recognition, CVPR'07

作者： Zhang Huang, Kaiqi Tan, Tieniu Wang, Liangsheng National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100080 China

ISBN: (纸本)1424411807

In this paper, a generic rule induction framework based on trajectory series analysis is proposed to learn the event rules. First the trajectories acquired by a tracking system are mapped into a set of primitive events that represent some basic motion patterns of moving object. Then a minimum description length (MDL) principle based grammar induction algorithm is adopted to infer the meaningful rules from the primitive event series. Compared with previous grammar rule based work on event recognition where the rules are all defined manually, our work aims to learn the event rules automatically. Experiments in a traffic crossroad have demonstrated the effectiveness of our methods. Shown in the experimental results, most of the grammar rules obtained by our algorithm are consistent with the actual traffic events in the crossroad. Furthermore the traffic lights rule in the crossroad can also be leaned correctly with the help of eliminating the irrelevant trajectories. © 2007 IEEE.

关键词： Logic programming

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Improved neural network based manifold learning method for face recognition with less face images per individual

Improved neural network based manifold learning method for f...

引用

2007 International Conference on Image Processing, computer vision, and pattern recognition, IPCV 2007

作者： Du, Chunhua Yang, Jie Wu, Zheng Yuan, Quan Wu, Qiang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Department of Computer Systems University of Technology Sydney Sydney Australia

ISBN: (纸本)9781601320438

In this paper, a novel neural network based manifold learning method(NNBML)[1] recently appeared in the Journal of Science is introduced. It can effectively convert high-dimensional data into low-dimensional codes, which are then used for classification. However, it performs not well while dealing with small size face database used for face recognition. We propose a solution generating more samples data based on the existing data. The proposed method is implemented on two well-known face databases, viz. ORL and Yale face databases. The experimental results show that NNBML is able to deal with the task of face recognition after more data samples generated using the proposed method, and also that NNBML outperforms LDA in terms of recognition rate.

关键词： Neural networks

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Facial strain pattern as a soft forensic evidence

Facial strain pattern as a soft forensic evidence

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7th IEEE Workshop on Applications of computer vision, WACV 2007

作者： Manohar, Vasant Goldgof, Dmitry Sarkar, Sudeep Yong, Zhang Computer Science and Engineering University of South Florida Tampa FL 33620 Computer Science and Information Systems Youngstown State University Youngstown OH 44555

ISBN: (纸本)0769527949

The success of forensic identification largely depends on the availability of strong evidence or traces that substantiate the prosecution hypothesis that a certain person is guilty of crime. In light of this, extracting subtle evidences which the criminals leave behind at the crime scene will be of valuable help to investigators. We propose a novel method of using strain pattern extracted from changing facial expressions in video as an auxiliary evidence for person identification. The strength of strain evidence is analyzed based on the increase in likelihood ratio it provides in a suspect population. Results show that strain pattern can be used as a supplementary biométric evidence in adverse operational conditions such as shadow lighting and face camouflage where pure intensity-based face recognition algorithms will fail. © 2007 IEEE.

关键词： Face recognition

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An attentional approach for perceptual grouping of spatially distributed patterns

引用

29th Annual Symposium of the German-Association-for-pattern-recognition

作者： Aziz, Muhammad Zaheer Mertsching, Baerbel Univ Gesamthsch Paderborn GET Lab Pohlweg 47-49 D-33098 Paderborn Germany

ISBN: (纸本)9783540749332

A natural (human) eye can easily detect large visual patterns or objects emerging from spatially distributed discrete entities. This aspect of pattern analysis has been barely addressed in literature. We propose a biologically inspired approach derived from the concept of visual attention to associate together the distributed pieces of macro level patterns. In contrast to the usual approach practiced by the existing models of visual attention, this paper introduces a short-term excitation on the features and locations related to the current focus of attention in parallel to the spatial inhibition of return. This causes the attention system to fixate on analogous units in the scene that may formulate a meaningful global pattern. It is evident from the results of experiments that the outcome of this process can help in widening the scope of intelligent machine vision.

关键词： vision

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Visual intelligence from vidgo and 3d sansor analytics

Visual intelligence from vidgo and 3d sansor analytics

引用

2007 IEEE computer Society Conference on computer vision and pattern recognition, CVPR'07

作者： Sawhney, Harpreet S. Vision and Learning Technologies Sarnoff Corporation Princeton NJ

ISBN: (纸本)1424411807

Video cameras are no ionger being used only in their traditional role of providing "Viewable pixels, but are rapidly becoming sources of intelligent information about the world. More recently 3D cameras are being developed to directly provide 3D measurements of objects and scenes. Appearance and geometry of objects and scenes, and the temporal dynamics of objects are the key information bearing sources for deriving visual intelligence. This talk will highlight sensor data analysis techniques for creating intelligent representations from 2D and 3D sensors. Intelligent sensor data analytics can be performed for mobile as well as widely distributed static sensor platforms. Applications ranging from 3D video manipulation, 3D situational awareness, wide area surveillance and tracking to video/3D object recognition and fingerprinting will be used to illustrate the work.

关键词： Video cameras

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On stabilisation of parametric active contours

On stabilisation of parametric active contours

引用

2007 IEEE computer Society Conference on computer vision and pattern recognition, CVPR'07

作者： Srikrishnan, V. Chaudhuri, Subhasis Roy, Sumantra Dutta Ševčovič, Daniel Vision and Image Processing Lab. EE Dept. I.I.T Bombay Mumbai India Dept. of Applied Math and Stats. Comenius University Bratislava Slovakia

ISBN: (纸本)1424411807

Parametric active contours have been used extensively in computer vision for different tasks like segmentation and tracking. However, all parametric contours are known to suffer from the problem of frequent bunching and spacing out of curve points locally during the curve evolution. In a spline based implementation of active contours, this leads to occasional formation of loops locally, and subsequently the curve blows up due to instabilities. It has been shown earlier that in addition to usual evolution along the normal direction, the curve should also be evolved in the tangential direction for stability purposes. In this paper, we provide a mathematical basis for selecting such a suitable tangential component for stabilisation. We prove the boundedness of the evolved curve in this paper, and provide the physical significance. We demonstrate the usefulness of the proposed method with a number of experiments. ©2007 IEEE.

关键词： Contour measurement

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Learning graph matching

Learning graph matching

引用

11th IEEE International Conference on computer vision

作者： Caetano, Tiberio S. Cheng, Li Le, Quoc V. Smola, Alex J. NICTA Stat Machine Learning Program Canberra ACT 0200 Australia

ISBN: (纸本)9781424416301

As a fundamental problem in pattern recognition, graph matching has found a variety of applications in the field of computer vision. In graph matching, patterns are modeled as graphs and pattern recognition amounts to finding a correspondence between the nodes of different graphs. There are many ways in which the problem has been formulated, but most can be cast in general as a quadratic assignment problem, where a linear term in the objective function encodes node compatibility functions and a quadratic term encodes edge compatibility functions. The main research focus in this theme is about designing efficient algorithms for solving approximately the quadratic assignment problem, since it is NP-hard. In this paper, we turn our attention to the complementary problem: how to estimate compatibility functions such that the solution of the resulting graph matching problem best matches the expected solution that a human would manually provide. We present a method for learning graph matching: the training examples are pairs of graphs and the "labels" are matchings between pairs of graphs. We present experimental results with real image data which give evidence that learning can improve the performance of standard graph matching algorithms. In particular, it turns out that linear assignment with such a learning scheme may improve over state-of-the-art quadratic assignment relaxations. This finding suggests that for a range of problems where quadratic assignment was thought to be essential for securing good results, linear assignment, which is far more efficient, could be just sufficient if learning is performed. This enables speed-ups of graph matching by up to 4 orders of magnitude while retaining state-of-the-art accuracy.

关键词： computer vision

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Intrackability theory and application

Intrackability theory and application

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5th International Symposium on Multispectral Image Processing and pattern recognition

作者： Li, Zheng Gong, Haifeng Sang, Nong Zhua, Gengming Huazhong Univ Sci & Technol Inst Pattern Recognit & Artificial Intelligence Wuhan Peoples R China Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing Peoples R China Hunan Univ Sci & Technol Sch Engn & Comp Sci Xiangtan Peoples R China

ISBN: (纸本)9780819469502

Many vision tasks can be posed as Bayesian inference, and the entropy of the posterior probability is a measure for uncertainty of perception, imperceptibility. In this paper, we studied the imperceptibility of multiple object tracking, intrackability. Entropy theory and Bayesian framework are used to represent multiple objects intrackability. Intrackability is computed by different kinds of tracking features. Feature selection is crucial for intrackability computation. An example of umbrellas tracking is shown in this paper. The intrackability which is computed by appearance and shape feature is compared. At last, we use intrackability to guide one application-- Automatic grouping. Objects are dynamically merged and tracked as a group when they come close to each other. Automatic grouping reduces the representation when some details can't be perceived. After the intrackable part of the representation is discarded, the computation is reduced.

关键词： intrackability object tracking automatic grouping

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Reduced memory zerotree envelop coding for wavelet image

Reduced memory zerotree envelop coding for wavelet image

引用

mippr 2007: Automatic Target recognition and Image Analysis;and Multispectral Image Acquisition

作者： Wentao, Wang Guoyou, Wang Jianguo, Liu State Key Lab. for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China College of Computer Science South-Central University for Nationalities 708 Minyuan Road Wuhan 430074 China

ISBN: (纸本)9780819469502

In this paper, we propose a new image codec, which called embedded zerotree wavelet coefficients envelop coding (EZWCEC). The coefficients envelop is characterized by describing the global tendency of the significant wavelet coefficients. Based on the empirical analysis and experimental results, our EZWCEC algorithm restores the trend of the significant wavelet coefficients and estimates the magnitude of some insignificant coefficients on the decoder. Unlike other zerotree coding algorithms such as Said and Pearlman's SPIHT using three lists, EZWCEC only uses two lists during encoding and decoding. So the memory requirement for the hardware implementation is reduced significantly. Although PSNR values for EZWCEC are lower than SPIHT's and JPEG2000's, our experiment results have shown that EZWCEC can dramatically improve the visual quality of reconstructed at low bit rates (e.g., below 0.1bpp).

关键词： Image coding

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A hierarchical model of shape and appearance for human action classification

A hierarchical model of shape and appearance for human actio...

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2007 IEEE computer Society Conference on computer vision and pattern recognition, CVPR'07

作者： Niebles, Juan Carlos Li, Fei-Fei Universidad Del Norte Colombia University of Illinois Urbana-Champaign United States Princeton University United States

ISBN: (纸本)1424411807

We present a novel model for human action categorization. A video sequence is represented as a collection of spatial and spatial-temporal features by extracting static and dynamic interest points. We propose a hierarchical model that can be characterized as a constellation of bags-of-features and that is able to combine both spatial and spatial-temporal features. Given a novel video sequence, the model is able to categorize human actions in a frame-by-frame basis. We test the model on a publicly available human action dataset [2] and show that our new method performs well on the classification task. We also conducted control experiments to show that the use of the proposed mixture of hierarchical models improves the classification performance over bag of feature models. An additional experiment shows that using both dynamic and static features provides a richer representation of human actions when compared to the use of a single feature type, as demonstrated by our evaluation in the classification task. © 2007 IEEE.

关键词： pattern recognition

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