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IEEE Conference on computer vision and pattern recognition

作者： Liu, Zhou Huang, Kaiqi Tan, Tieniu Wang, Liangsheng Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing Peoples R China

ISBN: (纸本)9781424411795

In this paper, we present a method using pixel-level information, local region-level information and global-level information to remove shadow. At the pixel-level, we employ GMM to model the behavior of cast shadow for every pixel in the HSV color space, as it can deal with complex illumination conditions. However, unlike the GMM for background which can obtain sample every frame, this model for shadow needs more frames to get the same number of sample, because shadow may not appear at the same pixel for each frame. Therefore, it will take a long time to converge. To overcome this drawback, we use the local region-level information to get more samples and global-level information to improve a preclassifier and then, by using it, we get samples which are more likely to be shadow. Also, at the local region-level, we use Markov random fields to represent dependencies between the label of single pixel and labels of its neighborhood. Moreover, to make global level information more robust, tracking information is used. Experimental results show that the proposed method is efficient and robust.

关键词： Feature extraction

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Sequential architecture for efficient car detection

Sequential architecture for efficient car detection

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IEEE Conference on computer vision and pattern recognition

作者： Zhu, Zhenfeng Zhao, Yao Lu, Hanqing Beijing Jiaotong Univ Inst Informat Sci Beijing Peoples R China Peking Univ Natl Key Lab Machine Percept Beijing Peoples R China Chinese Acad Sci Recongit Inst Automat Natl Lab Pattern Beijing Peoples R China

ISBN: (纸本)9781424411795

Based on multi-cue integration and hierarchical SVM, we present a sequential architecture for efficient car detection under complex outdoor scene in this paper. On the low level, two novel area templates based on edge and interest-point cues respectively are first constructed, which can be applied to forming the identities of visual perception to some extent and thus utilized to reject rapidly most of the negative non-car objects at the cost of missing few of the true ones. Moreover on the high level, both global structure and local texture cues are exploited to characterize the car objects precisely. To improve the computational efficiency of general SVM, a solution approximating based two-level hierarchical SVM is proposed. The experimental results show that the integration of global structure and local texture properties provides more power powerful ability in discrimination of car objects from non-car ones. The final high detection performance also contributes to the utilizing of two novel low level visual cues and the hierarchical SVM.

关键词： Object recognition

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Synthesising surface matching algorithms using the correspondence framework

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pattern recognition and Image Analysis 2007年第2期17卷 199-203页

作者： Planitz, B.M. Maeder, A.J. Williams, J.A. E-Health Research Centre CSIRO ICT Centre Level 20 300 Adelaide Street Brisbane QLD 4001 Australia School of Information Technology and Electrical Engineering University of Queensland St. Lucia QLD 4072 Australia

computer vision tasks such as registration, modeling and object recognition, are becoming increasingly useful in industry. Each of these applications employs correspondence algorithms to compute accurate mappings between partially overlapping surfaces. In industry, it is essential to select an appropriate correspondence algorithm for a given surface matching task. A correspondence framework has recently been proposed to assist in the selection and creation of correspondence algorithms for these tasks. This paper demonstrates how to use the correspondence framework to create a new surface matching algorithm, which uses stages of an existing model matching algorithm. The efficiency with which the new algorithm is created using the correspondence frame work is emphasized. In addition, results show that the new algorithm is both robust and efficient. © Nauka/Interperiodica 2007.

关键词： computer vision

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Real-time object classification in video surveillance based on appearance learning

Real-time object classification in video surveillance based ...

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IEEE Conference on computer vision and pattern recognition

作者： Zhang, Lun Li, Stan Z. Yuan, Xiaotong Xiang, Shiming Chinese Acad Sci Ctr Biomet & Secur Res Inst Automat Natl Lab Pattern Recognit Beijing 100080 Peoples R China

ISBN: (纸本)9781424411795

Classifying moving objects to semantically meaningful categories is important for automatic visual surveillance. However, this is a challenging problem due to the factors related to the limited object size, large intra-class variations of objects in a same class owing to different viewing angles and lighting, and real-time performance requirement in real-world applications. This paper describes an appearance-based method to achieve real-time and robust objects classification in diverse camera viewing angles. A new descriptor, i.e., the Multi-block Local Binary pattern (MB-LBP), is proposed to capture the large-scale structures in object appearances. Based on MB-LBP features, an adaBoost algorithm is introduced to select a subset of discriminative features as well as construct the strong two-class classifier To deal with the non-metric feature value of MB-LBP features, a multi-branch regression tree is developed as the weak classifiers of the boosting. Finally, the Error Correcting Output Code (ECOC) is introduced to achieve robust multi-class classification performance. Experimental results show that our approach can achieve real-time and robust object classification in diverse scenes.

关键词： Object recognition

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Human activity recognition based on ℜ transform

Human activity recognition based on ℜ transform

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

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

ISBN: (纸本)1424411807

This paper addresses human activity recognition based on a new feature descriptor. For a binary human silhouette, an extended radon transform, ℜ transform, is employed to represent low-level features. The advantage of the ℜ transform lies in its low computational complexity and geometric invariance. Then a set of HMMs based on the extracted features are trained to recognize activities. Compared with other commonly-used feature descriptors, ℜ transform is robust to frame loss in video, disjoint silhouettes and holes in the shape, and thus achieves better performance in recognizing similar activities. Rich experiments have proved the efficiency of the proposed method. © 2007 IEEE.

关键词： Gesture recognition

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An investigation of the modified direction feature for cursive character recognition

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pattern recognition 2007年第2期40卷 376-388页

作者： Blumenstein, Michael Liu, Xin Yu Verma, Brijesh Griffith Univ Sch Informat & Commun Technol Gold Coast Mail Centre Qld 9726 Australia Univ Cent Queensland Sch Informat Technol Rockhampton Qld 4702 Australia

This paper describes and analyses the performance of a novel feature extraction technique for the recognition of segmented/cursive characters that may be used in the context of a segmentation-based handwritten word recognition system. The modified direction feature (MDF) extraction technique builds upon the direction feature (DF) technique proposed previously that extracts direction information from the structure of character contours. This principal was extended so that the direction information is integrated with a technique for detecting transitions between background and foreground pixels in the character image. In order to improve on the DF extraction technique, a number of modifications were undertaken. With a view to describe the character contour more effectively, a re-design of the direction number determination technique was performed. Also, an additional global feature was introduced to improve the recognition accuracy for those characters that were most frequently confused with patterns of similar appearance. MDF was tested using a neural network-based classifier and compared to the DF and transition feature (TF) extraction techniques. MDF outperformed both DF and TF techniques using a benchmark dataset and compared favourably with the top results in the literature. A recognition accuracy of above 89% is reported on characters from the CEDAR dataset. (c) 2006 pattern recognition Society. Published by Elsevier Ltd. All rights reserved.

关键词： handwritten character recognition pattern recognition image processing and computer vision neural networks

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Automatic age estimation based on facial aging patterns

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IEEE TRANSACTIONS ON pattern ANALYSIS AND MACHINE INTELLIGENCE 2007年第12期29卷 2234-2240页

作者： Geng, Xin Zhou, Zhi-Hua Smith-Miles, Kate Deakin Univ Sch Informat Technol & Engn Melbourne Vic 3125 Australia Nanjing Univ Natl Key Lab Novel Software Technol Nanjing 210093 Peoples R China

While recognition of most facial variations, such as identity, expression, and gender, has been extensively studied, automatic age estimation has rarely been explored. In contrast to other facial variations, aging variation presents several unique characteristics which make age estimation a challenging task. This paper proposes an automatic age estimation method named AGES ( AGing pattern Subspace). The basic idea is to model the aging pattern, which is defined as the sequence of a particular individual's face images sorted in time order, by constructing a representative subspace. The proper aging pattern for a previously unseen face image is determined by the projection in the subspace that can reconstruct the face image with minimum reconstruction error, while the position of the face image in that aging pattern will then indicate its age. In the experiments, AGES and its variants are compared with the limited existing age estimation methods ( WAS and AAS) and some well- established classification methods (kNN, BP, C4.5, and SVM). Moreover, a comparison with human perception ability on age is conducted. It is interesting to note that the performance of AGES is not only significantly better than that of all the other algorithms, but also comparable to that of the human observers.

关键词： computer vision pattern recognition machine learning face and gesture recognition age estimation

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A fast 3D correspondence method for statistical shape Modeling

A fast 3D correspondence method for statistical shape Modeli...

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IEEE Conference on computer vision and pattern recognition

作者： Dalal, Pahal Munsell, Brent C. Wang, Song Tang, Jijun Oliver, Kenton Ninomiya, Hiroaki Zhou, Xiangrong Fujita, Hiroshi Univ South Carolina Dept Comp Engn & Sci Columbia SC 29208 USA Gifu Univ Grad Sch Med Div Regenerat & Adv Med Sci Dept Intelligent Image Informat Gifu Japan

ISBN: (纸本)9781424411795

Accurately identifying corresponded landmarks from a population of shape instances is the major challenge in constructing statistical shape models. In this paper, we address this landmark-based shape-correspondence problem for 3D cases by developing a highly efficient landmark-sliding algorithm. This algorithm is able to quickly refine all the landmarks in a parallel fashion by sliding them on the 3D shape surfaces. We use 3D thin-plate splines to model the shape-correspondence error so that the proposed algorithm is invariant to affine transformations and more accurately reflects the nonrigid biological shape deformations between different shape instances. In addition, the proposed algorithm can handle both open- and closed-surface shape, while most of the current 3D shape-correspondence methods can only handle genus-0 closed surfaces. We conduct experiments on 3D hippocampus data and compare the performance of the proposed algorithm to the state-of-the-art MDL and SPHARM methods. We find that, while the proposed algorithm produces a shape correspondence with a better or comparable quality to the other two, it takes substantially less CPU time. We also apply the proposed algorithm to correspond 3D diaphragm data which have an open-surface shape.

关键词： pattern recognition

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computer vision and pattern recognition in homeland security applications

Computer vision and pattern recognition in homeland security...

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7th International Workshop on Fuzzy Logic and Applications

作者： Garibotto, Giovanni B. Elsag Spa Genoa Italy

ISBN: (纸本)9783540733997

The tutorial will summarize the status of research and innovation in the field of Security of computer vision and pattern recognition Technology. Two main research areas are considered: intelligent scene analysis in video-surveillance, and mobile Automatic Number Plate recognition ANPR, for investigation and crime prevention. The lecture will refer the most recent advances of mobile ANPR solutions on board of patrol car as well as portable hand-held devices to improve mobility and flexibility. From the patrol car it is possible to collect vehicle information within the traffic flow with a performance that far exceeds human detection and recognition capabilities in all weather conditions and 24 It operation. Such a solution is currently used by most advanced police departments in the world.

关键词： computer vision pattern recognition video surveillance & security applications

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Learning in computer vision: Some thoughts

Learning in computer vision: Some thoughts

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12th Iberoamerican Congress on pattern recognition

作者： Petrou, Maria Univ London Imperial Coll Sci Technol & Med Dept Elect & Elect Engn Commun & Signal Proc Grp London SW7 2AZ England

ISBN: (纸本)9783540767244

It is argued that the ability to generalise is the most important characteristic of learning and that generalisation may be achieved only if pattern recognition systems learn the rules of meta-knowledge rather than the labels of objects. A structure, called "tower of knowledge", according to which knowledge may be organised, is proposed. A scheme of interpreting scenes using the tower of knowledge and aspects of utility theory is also proposed. Finally, it is argued that globally consistent solutions of labellings are neither possible, nor desirable for an artificial cognitive system.

关键词： computer vision

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