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检索条件"机构=Institute of Pattern Recognition & Image Processing"

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Head Pose Estimation from Low-Resolution image with Hough Forest

Head Pose Estimation from Low-Resolution Image with Hough Fo...

引用

Chinese Conference on pattern recognition (CCPR)

作者： Ming Zhang Ke Li Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

An approach for head pose estimation has been proposed in this paper using Hough forest. The estimation of pose are generated by voting from image patches as in a Hough transform. The basic idea is that image patches which contain eyes, hair or neck can give rich information about the head position and orientation. The voting process is implemented by randomized forest which is an efficient and robust tool for classification and regression. The method is quantitatively evaluated by comparing the estimated pose to the ground truth.

关键词： Head Estimation Training Uncertainty Humans Target tracking Computer vision

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A Bayesian framework for 3D human motion tracking from monocular image

A Bayesian framework for 3D human motion tracking from monoc...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Jian Liu Junchi Yan Minglei Tong Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

This paper addresses a strategy for 3D human motion recovery from monocular image. We advocate the use of Gaussian Process Dynamical Model (GPDM) for learning human pose and motion priors for 3D people tracking. With the prior learned from GPDM, we integrate our approach into a Bayesian tracking framework of condensation. During the off-line training step, a GPDM provides the reversible mappings between low-dimensional latent space and high-dimensional pose space, and then in the online tracking process, the latent variables are estimated via the particle filtering, and the observation is designed as a energy function based on a Markov Random Field (MRF) theory. The proposed approach is demonstrated on our database, and the experimental results show that our method performs promisingly.

关键词： Humans Three dimensional displays Tracking Shape image reconstruction Pixel Bayesian methods

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A hybrid image representation for indoor scene classification

A hybrid image representation for indoor scene classificatio...

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International Conference on image and Vision Computing New Zealand, IVCNZ

作者： Zhibin Niu Yue Zhou Kun Shi Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9781424496297

Although scene classification has been studied for decades, indoor scene recognition remains challenging due to its large view point variance and massive irregular artefacts. In fact, most existing methods for outdoor scene classification perform poorly in the indoor situation. To address the problem, we propose a hybrid image representation by combining the global information with the local structure of the scene. First, the global discriminative information is captured by pyramid GIST feature. Second, the local structure is encoded by the bag of features method with Histogram Intersection Kernel (HIK). Finally, HIK based SVM is employed for learning and classification. Experiments on the MIT indoor scene database show that our approach could significantly improve the recognition accuracy of the state-of-art methods by about 14%.

关键词： Support vector machines

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Visual saliency detection via rank-sparsity decomposition

Visual saliency detection via rank-sparsity decomposition

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IEEE International Conference on image processing

作者： Junchi Yan Jian Liu Yin Li Zhibin Niu Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

Saliency mechanism has been considered crucial in the human visual system and helpful to object detection and recognition. This paper addresses a novel feature-based model for visual saliency detection. It consists of two steps: first, using the learned overcomplete sparse bases to represent image patches; and then, estimating saliency information via direct low-rank and sparsity matrix decomposition. We compare our model with the previous methods on natural images. Experimental results show that our model performs competitively for visual saliency detection task, and suggest the potential application of matrix decomposition and convex optimization for image analysis.

关键词： Matrix decomposition Sparse matrices Visualization Dictionaries Humans Convex functions Encoding

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Research on Fuzzy C Switching Regression Model with Generalized Improved Fuzzy Partitions

Research on Fuzzy C Switching Regression Model with Generali...

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Chinese Conference on pattern recognition (CCPR)

作者： Beibei Qin Lin Zhu Jie Yang Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

By introducing a novel membership constraint function, a new algorithm called fuzzy c-means switching regression model with generalized improved fuzzy partitions (GIFP-FCRM) is proposed. This algorithm seems less sensitive to noise and outliers than the classical fuzzy C switching regression model (FCRM), and provides a generalized model with the fuzziness index m for the fuzzy C switching regression model with improved fuzzy partitions (IFP-FCRM). Furthermore, with fuzzy parameter α, the classical FCRM and IFP-FCRM can be taken as two special cases of the proposed algorithm. Several experimental results are presented to demonstrate its advantage over FCRM in both noise insensitivity and robustness capability.

关键词： Switches Partitioning algorithms Clustering algorithms pattern recognition Biological system modeling image processing Artificial intelligence

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Conotoxin Superfamily Prediction Based on Diffusion Maps and dHKNN

Conotoxin Superfamily Prediction Based on Diffusion Maps and...

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Chinese Conference on pattern recognition (CCPR)

作者： Jiang-Bo Yin Jian-Bo Lei Yong-Xian Fan Hong-Bin Shen Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

Conotoxins show prospects for being potent pharmaceuticals in the treatment of some serious disease. Accurate prediction of conotoxin superfamily would have many important applications in biological research and clinical medicine. In this study, we propose a novel dHKNN method to predict conotoxin superfamily. Firstly, we extract the protein's sequential features composed of physicochemical properties, evolutionary information, predicted secondary structures and amino acid composition. Then we use the diffusion maps for dimensionality *** last, with considering the local density information in the diffusion space, the dHKNN is proposed based on the K-local hyperplane distance nearest neighbor subspace classifier method for predicting conotoxin superfamilies. An overall accuracy of 91.90% is obtained through the jackknife cross-validation test which is higher than present methods.

关键词： Proteins Bioinformatics Amino acids Accuracy Databases Gene expression

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3D space-time detection based control points selection of DSA

3D space-time detection based control points selection of DS...

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2010 2nd Pacific-Asia Conference on Circuits, Communications and System, PACCS 2010

作者： Zhang, Fan Li, Bo Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475001 China

ISBN: (纸本)9781424479689

A 3D space-time motion detection based DSA control point selection algorithm is proposed. Main content is to detect the movement of image points based on the control selection and registration algorithm and using DSA image sequences to speed up the registration of control points. The image features, such as the edge, are used as the control points to register image effectively. According to the location of control points, 3D space-time characteristics are used to search control points, and it will further reduce the number of control points, and make the control point registration more accurate. © 2010 IEEE.

关键词： 3D space-time characteristics 3D space-time detection 3D space-time detection 3D space-time motion detection DSA control point selection algorithm DSA image sequences control point registration control points control points registration control points selection control selection diagnostic radiography digital subtraction angiography image features image points image registration image registration image sequences medical image processing motion compensation registration algorithm

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Matching based Highlight Removal

Matching based Highlight Removal

引用

International Conference on Multimedia Technology

作者： Yiren Xu Fujian Wang Yuming Zhao Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

This paper presents a three-step framework to remove the highlight exists on objects in certain conditions. Unlike traditional HDR (High Dynamic Range) technology requires multiple registrated image sequence; our method needs only two arbitrary images. SURF (Speeded Up Robust Features) matching algorithm is first applied to find corresponding point pairs between images; homography is then found by perspective transformation theory; minimum gray selection is used at last to eliminated the highlight and fuse related regions. Experimental results are given to demonstrate the performance of our method.

关键词： Feature extraction image color analysis Robustness Dynamic range Plastics Pixel Color

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A Study of Geometric Features for Aging Face recognition

A Study of Geometric Features for Aging Face Recognition

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Chinese Conference on pattern recognition (CCPR)

作者： Xiaoqian Chen Pengfei Shi Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

Human facial shapes undergo significant variations from infancy to teenage, while they change limitedly as people age into adulthood. In this paper, facial shapes of males across ages using Euclidean distances are studied and a D-A standard (Distance related to Ages) is proposed for this purpose. Further, we determine the distance features that significantly contribute to the aging face recognition. Experimental results using the MORPH database containing age separated facial images are encouraging and illustrate Euclidean distance features improve the performance of face recognition across ages.

关键词： Support vector machines Face recognition Face Computer vision Principal component analysis Aging Shape

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Feature Fusion and Selection for Recognizing Cancer-Related Mutations from Common Polymorphisms

Feature Fusion and Selection for Recognizing Cancer-Related ...

引用

Chinese Conference on pattern recognition (CCPR)

作者： Jian-Bo Lei Jiang-Bo Yin Hong-Bin Shen Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

Single nucleotide polymorphisms (SNPs) are the most common form of genetic variant in humans, which can be generally classified into disease related mutations and common ones. It has been generally accepted that SNPs caused amino acid substitutions are of particular interest as candidates for affecting susceptibility to complex diseases, such as cancer, which is a serious public issue affecting millions of people worldwide each year. In this study, we have developed an automated and robust method to distinguish cancer-related mutations from common polymorphisms from amino acid sequence, which has a significant meaning for the cancer diagnosis, prognosis and treatment. Multiple different sequential features are extracted and the most important features are finally selected for constructing the prediction model. Experimental results show that an overall 81.07% success rate has been obtained, indicating the proposed method is very promising in the clinical cancer research studies.

关键词： Proteins Cancer Amino acids Feature extraction Support vector machines Databases Accuracy

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