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A swarm intelligence based searching strategy for articulated 3D human body tracking

A swarm intelligence based searching strategy for articulate...

引用

2010 IEEE computer Society Conference on computer Vision and pattern recognition - Workshops, CVPRW 2010

作者： Zhang, Xiaoqin Hu, Weiming Wang, Xiangyang Kong, Yu Xie, Nianhua Wang, Hanzi Ling, Haibin Maybank, Steve College of Mathematics and Information Science Wenzhou University Zhejiang China National Laboratory of Pattern Recognition Institute of Automation Beijing China School of Communication and Information Engineering Shanghai University Shanghai China School of Computer Science Beijing Institute of Technology Beijing China School of Computer Science University of Adelaide Australia Department of Computer and Information Science Temple University Philadelphia United States School of Computer Science and Information Systems Birkbeck College London United Kingdom

ISBN: (纸本)9781424470297

This paper proposes an annealed particle swarm optimization based particle filter algorithm for articulated 3D human body tracking. In our algorithm, a sampling covariance and an annealing factor are incorporated into the velocity updating equation of particle swarm optimization (PSO). The sampling covariance and the annealing factor are initiated with appropriate values at the beginning of the PSO iteration, and 'annealing' is carried out at reasonable steps. Experiments with multi-camera walking sequences from the Brown dataset show that: 1) the proposed tracker can effectively alleviate the problem of inconsistency between the image likelihood and the true model;2) the tracker is also robust to noise and body self-occlusion. © 2010 IEEE.

关键词： Swarm intelligence

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Virtual housing design experience platform

Virtual housing design experience platform

引用

International Conference on Multimedia Technology

作者： Dai, Dameng Ding, Jianhao Wang, Yigang College of Physics and Electronic Information and Engineering Wenzhou University Wenzhou China Institute of Computer Graphics and Image Processing Hangzhou Dianzi University Hangzhou China State Key Laboratory of CAD and CG Zhejiang University Hangzhou China

ISBN: (纸本)9781424478743

Traditional display fashions of housing design mainly depend on static pictures, which are short of the intuition of house space and do not support interaction during design periods. This paper proposes a virtual housing design experience platform consist of a cheap hardware VR environment and housing design software system we developed. With this design platform, a fast generating virtual house permits intuitive and precise interaction in the VR environment. Customers can modify the design of their home and have a pseudo experience of their virtual house in real time. The system will give advice on layout design, providing a complete and precise house space representation and the support for real time visualization. ©2010 IEEE.

关键词： Virtual reality

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A method for improving the accuracy of predicting protein localization

A method for improving the accuracy of predicting protein lo...

引用

The 5th International Conference on computer Science & Education(第五届国际计算机新技术与教育学术研讨会 ICCSE'10)

作者： Tong Wang Qinghua Huang Lixiu Yao Institute of Computer and Information Shanghai Second Polytechnic UniversityShanghai201209China School of Communication and Information Engineering Shanghai University Shanghai200444China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong UniversityShanghai200240C

In this paper, a system based on the novel Maximum Variance Projection (MVP) is proposed to improve the performance of protein subcellular localization prediction. Firstly, the protein sequences are quantized into a high dimension space using a new representation approach Position-Specific Score Matrix (PSSM). However, the problems caused by such representation are computation complexity and complicated classifier design. To sort out this problem, a new dimension reduction algorithm, MVP, is introduced. It extracts the essential features from the high dimension feature space. Then, K-Nearest Neighbor (K-NN) classifier is employed to recognize the subcellular localization of proteins according to the new features after dimension reduction. A good experimental result is obtained based on the jackknife dataset.

关键词： Subcellular localization:Dimensionality reduction:PSSM

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A dorsal hand vein pattern recognition algorithm

A dorsal hand vein pattern recognition algorithm

引用

Congress on image and Signal processing, CISP

作者： Xi Li Xiangbin Liu Zhicheng Liu College of Math and Computer Science Hunan Normal University Changsha China Institute of Image Recognition & Computer Vision Hunan Normal University China School of Information Science and Engineering Central South University Changsha China Institute of Image Recognition & Computer Vision Hunan Normal University Changsha China

An algorithm for dorsal hand vein pattern recognition is presented in the paper. To improve the recognition ratio, the vein skeleton extracting with little distortion is very important. Firstly, the algorithm acquires a clean, one-pixel-width skeleton with little distortion after a series of processes: size and gray normalizing, Gaussian lowpass and median filtering, NiBlack local dynamic thresholding segmenting, area thresholding, morphological opening and closing, median filtering, conditional thinning, spurs pruning. Then, the seven corrected moment invariants of the vein skeleton are extracted as the feature vector. At last, the feature vector is input into SVM for training and recognition. Experiment shows the algorithm achieves a higher recognition ratio of 95.5%.

关键词： Veins Feature extraction Skeleton pattern recognition Pixel image segmentation Support vector machines

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The method of image restoration in the environments of dust

The method of image restoration in the environments of dust

引用

IEEE International Conference on Mechatronics and Automation

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education TaiYuan University of Technology TaiYuan China College of Mechanical Engineering TaiYuan University of Technology TaiYuan China Institute for Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology WuHan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, a particle swarm optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with dual threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.

关键词： image edge detection image restoration Degradation Atmospheric modeling Optical scattering Optical imaging

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Study on the Method of image Restoration in the Environment of Dust

Study on the Method of Image Restoration in the Environment ...

引用

International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education Taiyuan University Of Technology Taiyuan China College of Mechanical Engineering Taiyuan University Of Technology Taiyuan China Institute of Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control HuaZhong University of Science and Technology Wuhan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, GA optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with automatic threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.

关键词： image edge detection image restoration Scattering Degradation Gallium Atmospheric modeling Genetic algorithms

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An image-Sequence Compressing Algorithm Based on Homography Transformation for Unmanned Aerial Vehicle

An Image-Sequence Compressing Algorithm Based on Homography ...

引用

International Symposium on Intelligence information processing and Trusted Computing (IPTC)

作者： Junbin Gong Chenlin Zheng Jinwen Tian Dingxue Wu Institute for Pattern Recognition and Artificial Intelligence National key laboratory of science and technology on multi-spectral information processing Huazhong University of Science and Technology Wuhan China College of Computer Science and Technology Huanggang Normal University Huangang China

Focus on the image compressing problem of unmanned aerial vehicle with high compression ratio, fixed compressing ratio and low computational complexity requirement, a low-complexity image-sequence compressing algorithm based on homography transformation was proposed. The image sequences were dynamically divided into frame-groups according the data from airborne inertial navigation systems, and the intermediate frames in the same frame-group was b i-directionally predicted by the first-frame and the end-frame with homography transformation. The homography matrix was got approximately by the airborne inertial navigation systems firstly and then was accurately computed by fast multiple sub-areas template matching. At the end the first frame and the residual images of the intermediate frames of the same frame-group was merged into a big image and coded by JPEG2000 to generate fixed-size code streams. The experiment results show that the proposed algorithm was with high compression performance, low computational complexity and excellent capacity for code-size control and will has good prospect in engineer.

关键词： image coding Unmanned aerial vehicles Cameras Transform coding image restoration image sequences Heuristic algorithms

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A swarm intelligence based searching strategy for articulated 3D human body tracking

A swarm intelligence based searching strategy for articulate...

引用

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

作者： Xiaoqin Zhang Weiming Hu Xiangyang Wang Yu Kong Nianhua Xie Hanzi Wang Haibin Ling Steve Maybank College of Mathematics & Information science Wenzhou University Zhejiang China Institute of Automation National Laboratory of Pattern Recognition Beijing China School of Communication and Information Engineering Shanghai University Shanghai China School of Computer Science Beijing Institute of Technology Beijing China School of Computer Science University of Adelaide Australia Department of Computer and Information Science Temple University Philadelphia USA School of Computer Science and Information Systems Birkbeck College London UK

This paper proposes an annealed particle swarm optimization based particle filter algorithm for articulated 3D human body tracking. In our algorithm, a sampling covariance and an annealing factor are incorporated into the velocity updating equation of particle swarm optimization (PSO). The sampling covariance and the annealing factor are initiated with appropriate values at the beginning of the PSO iteration, and `annealing' is carried out at reasonable steps. Experiments with multi-camera walking sequences from the Brown dataset show that: 1) the proposed tracker can effectively alleviate the problem of inconsistency between the image likelihood and the true model; 2) the tracker is also robust to noise and body self-occlusion.

关键词： Particle swarm optimization Humans Annealing Particle filters Particle tracking Sampling methods Equations image sampling Legged locomotion Noise robustness

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数字媒体技术专业实训规划的探讨

数字媒体技术专业实训规划的探讨

引用

第21届全国计算机新科技与计算机教育学术大会

作者： YANG Xinxin 杨欣欣 ZHOU Bing 周兵 MIAO Ru 苗茹 School of Computer and Information Engineering Henan University Kaifeng 475004 河南大学计算机与信息工程学院开封475004 Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475004 河南大学图像处理与模式识别研究所开封475004

本文以河南大学计算机与信息工程学院的数字媒体技术专业的校内实训为例，探讨了如何对数字媒体技术专业进行实训。本文首先论述了实训规划，并以视频短片为例子进行了详细说明。其次通过实训效果和实训经验的总结，得出了下一步工作应... 详细信息

本文以河南大学计算机与信息工程学院的数字媒体技术专业的校内实训为例，探讨了如何对数字媒体技术专业进行实训。本文首先论述了实训规划，并以视频短片为例子进行了详细说明。其次通过实训效果和实训经验的总结，得出了下一步工作应该做些什么的结论。

关键词：高等院校数字媒体技术专业视频教学实训效果

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Improved rice algorithm of lossless compression for on-board images

Improved rice algorithm of lossless compression for on-board...

引用

International Conference on Multimedia Technology

作者： Wei, Yong-Wang Ding, Qing-Hai Luo, Hai-Bo Shenyang Institute of Automation Chinese Academy of Science Shenyang 110016 China Graduate School of Chinese Academy of Science Beijing 100049 China Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Science Shenyang 110016 China Key Laboratory of Image Understanding and Computer Vision Liaoning Province 110016 China Electrical and Information Engineering College Beihua University Jilin 132021 China Research Institute of General Development and Demonstration of Equipment Equipment Academy of Air Force Beijing100076 China

ISBN: (纸本)9781424478743

Aiming at the problems of the relatively lower compression ratio and the difficulty in hardware implementation regarding Rice lossless compression algorithm for the Space-borne Remote-sensing images, an improved Rice method is proposed in which the length of predictor FIFO is determined by the size of input images and the global unicode for differences is used. The improved Rice algorithm is mainly composed of two steps, MED prediction for the whole row data and Rice global uniform entropy coding. The statistical results show that it can significantly reduce the spatial redundancy of the adjacent pixels and the mean value of image differences. The compression bit rate is reduced approximately 0.4581 bpp(bit/pixel) against the original Rice algorithm. Furthermore, the new way reserves the all detail information of the input images throughout the whole encoding process. Because we split the all samples with the same mode, the proportion of the identifier of the splitting mechanic in the output data stream is reduced and the compression ratio is increased. The improvement can reduce the encoding complexity and be easily implemented for hardware application. ©2010 IEEE.

关键词： Signal encoding

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