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2007 ieee computer society conference on computer vision and pattern recognition, CVPR'07

作者： Li, Yang Tan, Tiow-Seng Volkau, Hiar Nowinski, Wieslaw L. Department of Computer Science National University of Singapore Biomedical Imaging Lab. Singapore Bioimaging Consortium

ISBN: (纸本)1424411807

This paper proposes a novel model-guided segmentation framework utilizing a statistical surface wavelet model as a shape prior. In the model building process, a set of training shapes are decomposed through the subdivision surface wavelet scheme. By interpreting the resultant wavelet coefficients as random variables, we compute prior probability distributions of the wavelet coefficients to model the shape variations of the training set at different scales and spatial locations. With this statistical shape model, the segmentation task is formulated as an optimization problem to best fit the statistical shape model with an input image. Due to the localization property of the wavelet shape representation both in scale and space, this multi-dimensional optimization problem can be efficiently solved in a multiscale and spatial-localized manner. We have applied our method to segment cerebral caudate nuclei from MRI images. The experimental results have been validated with segmentations obtained through human expert. These show that our method is robust, computationally efficient and achieves a high degree of segmentation accuracy. © 2007 ieee.

关键词： Image segmentation

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Learning the compositional nature of visual objects

Learning the compositional nature of visual objects

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2007 ieee computer society conference on computer vision and pattern recognition, CVPR'07

作者： Yuan, Quan Thangali, Ashwin Ablavsky, Vitaly Sclaroff, Stan Computer Science Department Boston University 111 Cummington Street Boston MA 02215

ISBN: (纸本)1424411807

Object detection can be challenging when the object class exhibits large variations. One commonly-used strategy is to first partition the space of possible object variations and then train separate classifiers for each portion. However, with continuous spaces the partitions tend to be arbitrary since there are no natural boundaries (for example, consider the continuous range of human body poses). In this paper, a new formulation is proposed, where the detectors themselves are associated with continuous parameters, and reside in a parameterized function space. There are two advantages of this strategy. First, a-priori partitioning of the parameter space is not needed;the detectors themselves are in a parameterized space. Second, the underlying parameters for object variations can be learned from training data in an unsupervised manner. In profile face detection experiments, at a fixed false alarm number of 90, our method attains a detection rate of 75% vs. 70% for the method of Viola-Jones. In hand shape detection, at a false positive rate of 0.1%, our method achieves a detection rate of 99.5% vs. 98% for partition based methods. In pedestrian detection, our method reduces the miss detection rate by a factor of three at a false positive rate of 1%, compared with the method of Dalal-Triggs. ©2007 ieee.

关键词： Object recognition

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The tower of knowledge scheme for learning in computer vision

The tower of knowledge scheme for learning in computer visio...

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Australian pattern recognition society (APRS)

作者： Petrou, Maria Xu, Mai Communications and Signal Processing Group Electrical and Electronic Engineering Department Imperial College London Exhibition Road London SW7 2AZ United Kingdom

A scheme, named tower of knowledge (ToK), is proposed for interpreting 3D scenes. The ToK encapsulates causal dependencies between object appearance and functionality. We demonstrate it by labelling the components of ... 详细信息

ISBN: (纸本)0769530672

关键词： Three dimensional computer graphics

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A new segmentation method for MRI images of the shoulder joint

A new segmentation method for MRI images of the shoulder joi...

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4th Canadian conference on computer and Robot vision, CRV 2007

作者： Nguyen, Nhat Tan Laurendeau, Denis Branzan-Albu, Alexandra Computer Vision and Systems Laboratory Laval University Que. Canada Computer Vision Laboratory University of Victoria Vic. Canada

ISBN: (纸本)0769527868

This paper presents an integrated region-based and gradient-based supervised method for segmentation of a patient magnetic resonance images (MRI) of the shoulder joint. The method is noninvasive, anatomy-based and requires only simple user interaction. It is generic and easily customizable for a variety of routine clinical uses in orthopedic surgery. © 2007 ieee.

关键词： Image segmentation

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Visual speech recognition and utterance segmentation based on mouth movement

Visual speech recognition and utterance segmentation based o...

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Australian pattern recognition society (APRS)

作者： Yau, Wai Chee Weghorn, Hans Kumar, Dinesh Kant Information Technology BA-University of Cooperative Education Stuttgart Germany School of Electrical and Computer Engineering RMIT University Melbourne Australia

ISBN: (纸本)0769530672

This paper presents a vision-based approach to recognize speech without evaluating the acoustic signals. The proposed technique combines motion features and support vector machines (SVMs) to classify utterances. Segmentation of utterances is important in a visual speech recognition system. This research proposes a video segmentation method to detect the start and end frames of isolated utterances from an image sequence. Frames that correspond to 'speaking' and 'silence' phases are identified based on mouth movement information. The experimental results demonstrate that the proposed visual speech recognition technique yields high accuracy in a phoneme classification task. Potential applications of such a system are, e.g., human computer interface (HCI) for mobility-impaired users, lip-reading mobile phones, in-vehicle systems, and improvement of speech-based computer control in noisy environments. © 2007 ieee.

关键词： Support vector machines

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Fiber tract clustering on manifolds with dual rooted-graphs

Fiber tract clustering on manifolds with dual rooted-graphs

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2007 ieee computer society conference on computer vision and pattern recognition, CVPR'07

作者： Tsai, Andy Westin, Carl-Fredrik Hero III, Alfred O. Willsky, Alan S. Dept. of Radiology Brigham and Women's Hospital Harvard Medical School Boston MA 02115 Dept. of Electrical Eng. and Computer Science Mass. Institute of Technology Cambridge MA 02139 Dept. of Electrical Eng. and Computer Science University of Michigan Ann Arbor MI 48109

ISBN: (纸本)1424411807

We propose a manifold learning approach to fiber tract clustering using a novel similarity measure between fiber tracts constructed from dual-rooted graphs. In particular, to generate this similarity measure, the chamfer or Hausdorff distance is initially employed as a local distance metric to construct minimum spanning trees between pairwise fiber tracts. These minimum spanning trees are effective in capturing the intrinsic geometry of the fiber tracts. Hence, they are used to capture the neighborhood structures of the fiber tract data set. We next assume the high-dimensional input fiber tracts to lie on low-dimensional non-linear manifolds. We apply Locally Linear Embedding, a popular manifold learning technique, to define a low-dimensional embedding of the fiber tracts that preserves the neighborhood structures of the high-dimensional data structure as captured by the method of dual-rooted graphs. Clustering is then performed on this low-dimensional data structure using the k-means algorithm. We illustrate our resulting clustering technique on both synthetic data and on real fiber tract data obtained from diffusion tensor imaging. © 2007 ieee.

关键词： Clustering algorithms

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Proceeding of the ieee computer Scoeity conference on computer vision and pattern recognition: Preface

Proceedings of the IEEE Computer Society Conference on Compu...

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Proceedings of the ieee computer society conference on computer vision and pattern recognition 2007年

作者： Bhanu, Bir Ratha, Nalini University of California Riverside IBM T. J. Watson Research Center

No abstract available

ISBN: (纸本)1424411807

No abstract available

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Proceedings - Digital Image Computing Techniques and Applications: 9th Biennial conference of the Australian pattern recognition society, DICTA 2007

Proceedings - Digital Image Computing Techniques and Applica...

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Australian pattern recognition society (APRS)

ISBN: (纸本)0769530672

The proceedings contain 87 papers. The topics discussed include: recognition of facial movements and hand gestures using surface electromyogram(sEMG) for HCI based applications;visual speech recognition and utterance segmentation based on mouth movement;limitations and applications of ICA in facial sEMG and hand gesture sEMG for human computer interaction;interactive reconstruction of archaeological fragments in a collaborative environment;subtle hand gesture identification for HCI using temporal decorrelation source separation BSS of surface EMG;interactive visual guide system for learning manual work;robust histogram-based object tracking in image sequences;enhancing video surveillance with audio events;region based maximum likelihood estimation for small geospatial object extraction;simplex optimization initialized by gaussian mixture for active appearance models;and the tower of knowledge scheme for learning in computer vision.

关键词： Human computer interaction

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A decoupled algorithm for vision parameter estimation with application to the trifocal tensor

A decoupled algorithm for vision parameter estimation with a...

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Australian pattern recognition society (APRS)

作者： Scoleri, Tony Chojnacki, Wojciech Brooks, Michael J. Defence Science and Technology Organisation Edinburgh SA 5111 Australia School of Computer Science University of Adelaide Adelaide SA 5005 Australia

ISBN: (纸本)0769530672

We consider the problem of estimating parameters of a model described by a system of equations which underlies a wide class of computer vision applications. One method to solve such a problem is the fundamental numerical scheme (FNS) previously proposed by some of the authors. In this paper, a more stable version of FNS is developed, with better convergence properties than the original version. The improvement in performance is achieved by reducing the original estimation problem to a couple of problems of lower dimension. By way of example, the new algorithm has been applied to the problem of estimating the trifocal tensor relating three views of a scene. Experiments carried out with both synthetic and real images reveal the new estimator to be more stable compared to the original FNS method, and commensurate in accuracy with the Gold Standard maximum likelihood estimator. © 2007 Crown Copyright.

关键词： Parameter estimation

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A real-time hand gesture recognition method

A real-time hand gesture recognition method

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ieee International conference onMultimedia and Expo, ICME 2007

作者： Yikai, Fang Kongqiao, Wang Jian, Cheng Hanqing, Lu National Lab. of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100080 China Nokia Research Center Nokia House 1 No.11 He Ping Li Dong Jie Beijing 100013 China

ISBN: (纸本)1424410177

Compared with the traditional interaction approaches, such as keyboard, mouse, pen, etc, vision based hand interaction is more natural and efficient. In this paper, we proposed a robust real-time hand gesture recognition method. In our method, firstly, a specific gesture is required to trigger the hand detection followed by tracking;then hand is segmented using motion and color cues;finally, in order to break the limitation of aspect ratio encountered in most of learning based hand gesture methods, the scale-space feature detection is integrated into gesture recognition. Applying the proposed method to navigation of image browsing, experimental results show that our method achieves satisfactory performance. © 2007 ieee.

关键词： Gesture recognition

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