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40th IEEE International Conference on Acoustics, Speech, and Signal processing, ICASSP 2015

作者： Xu, Wei Li, Yijun Gong, Chen Yang, Jie Institution of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

ISBN: (纸本)9781467369978

Implicit camera transfer (ICT), which models the multi-valued mappings between two specific and stationary cameras, is a descent solution for the person re-identification problem of the surveillance system. It has the properties of simplicity, computational efficiency and well utilizing negative training data. But it neglects the complementary relation between the descriptors of various views. And different appearance people have various most discriminative views among all the views, which are under diverse mappings. To tackle with this constraint, we model the multi-values mapping from different view independently, and fuse these transferring results of each view by LPBoost. Experimental results demonstrate that our scheme not only inherits most of the advantages (some sacrifice in speed, but still can run in real time for the same testing case in the ICT paper) of ICT but also obtains more discriminative mappings than ICT. In addition, our solution gains competitive performance on 2 challenging datasets. © 2015 IEEE.

关键词： implicit camera transfer multi-view fusing person re-identification

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Pedestrian counting based on spatial and temporal analysis

Pedestrian counting based on spatial and temporal analysis

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作者： Yu, Zhongjie Gong, Chen Yang, Jie Bai, Li Institution of Image Processing and Pattern Recognition Shanghai Jiao Tong University China University of Nottingham United Kingdom

ISBN: (纸本)9781479957514

Pedestrian counting is an important component of video processing. Existing works with overhead cameras are mainly based on visual tracking, the robustness of which is rather limited. By proposing the novel spatial-temporal matrix, this paper aims to count pedestrians without tracking. As a result, a more robust and efficient pedestrian counting algorithm can be developed. Extensive experiment reveal that our system achieves satisfying performances in terms of both accuracy and efficiency. © 2014 IEEE.

关键词： Security systems

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Total variation-based speckle reduction using multi-grid algorithm for ultrasound images

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13th International Conference on image Analysis and processing, ICIAP 2005

作者： Sheng, Chen Xin, Yang Liping, Yao Kun, Sun Institution of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Shanghai Children's Medical Center Shanghai Second Medical University Shanghai China

ISBN: (纸本)3540288694

This paper presents an approach for speckle reduction and coherence enhancement of ultrasound images based on total variation (TV) minimization. The proposed method can preserve information associated with resolved object structures while reducing the speckle noise. However, since the equation system deduced by the TV-based method is a strongly nonlinear partial differential equation (PDE) system, the convergence rate is very slow when using standard numerical optimization techniques. So in this paper, we introduce the nonlinear multi-grid algorithm to solve this system. Numerical results indicate that the image can be recovered with satisfied result even contamination of strong noise using the proposed method and the algorithm of nonlinear multi-grid has more efficiency than the conventional numerical techniques such as conjugate gradient (CG). © Springer-Verlag Berlin Heidelberg 2005.

关键词： Speckle

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Segmentation in echocardiographic sequences using shape-based snake model

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13th International Conference on image Analysis and processing, ICIAP 2005

ISBN: (纸本)3540288694

A novel method for segmentation of cardiac structures in temporal echocardiographic sequences based on the snake model is presented. The method is motivated by the observation that the structures of neighboring frames have consistent locations and shapes that aid in segmentation. To cooperate with the constraining information provided by the neighboring frames, we combine the template matching with the conventional snake model. Furthermore, in order to auto or semi-automatically segment the sequent images without manually drawing the initial contours in each image, generalized Hough transformation (GHT) is used to roughly estimate the initial contour by transforming the neighboring prior shape. As a result, the active contour can easily detect the desirable boundaries in ultrasound images. © Springer-Verlag Berlin Heidelberg 2005.

关键词： image segmentation

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Augmented broadcaster identity-based broadcast encryption

Journal of Digital Information Management

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Journal of Digital Information Management 2013年第3期11卷 227-234页

作者： Zhang, Jianhong Xu, Yuwei Chen, Zhipeng Institution of Image Processing and Pattern Recognition North China University of Technology Beijing 100144 China

Identity-based Broadcast Encryption (IBBE) has the inherent key escrow problem that Private Key Generator (PKG) can fully determine the user's private key, which is an obstacle of the application of IBBE. The existing approaches to solving key escrow problem need the user to submit identity to multiple PKGs or interactions between PKG and the user in the private key extraction phase. For Point-to-Multipoint Identity-based Broadcast Encryption (P2MIBBE) that the computing capabilities of receiver are limited, these approaches are impracticable. We propose a new approach what we call Augmented Broadcaster Identity-based Broadcast Encryption (ABIBBE). It requires neither multiple PKGs nor calculation of receiver in the private key extraction phase. We construct a universal scheme to realize AB-IBBE, such that any IND-ID-CPA secure IBBE scheme can be extended to an IND-ID-CPA secure AB-IBBE scheme.

关键词： Extraction

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ABNORMAL EVENT DETECTION USING SPATIO-TEMPORAL FEATURE AND NONNEGATIVE LOCALITY-CONSTRAINED LINEAR CODING

ABNORMAL EVENT DETECTION USING SPATIO-TEMPORAL FEATURE AND N...

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IEEE International Conference on image processing

作者： Yu Zhao Lei Zhou Keren Fu Jie Yang Institution of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

ISBN: (纸本)9781467399623

In this paper, an approach using the spatio-temporal feature and nonnegative locality-constrained linear coding (NLLC) is proposed to detect abnormal events in videos. This approach utilizes position-based spatio-temporal descriptors as the low-level representations of a video clip. Each descriptor consists of the position information of a space-time interest point and an appearance feature vector. To obtain the high-level video representations, the nonnegative locality-constrained linear coding is adopted to encode each spatio-temporal descriptor. Then, the max pooling integrates all NLLC codes of a video clip to produce a feature vector. Finally, the support vector machine (SVM) is employed to classify the feature vector as abnormal or normal. Experimental results on two datasets have demonstrated the promising performance of the proposed approach in the detection of both global and local abnormal events.

关键词： Videos Encoding Feature extraction Event detection Support vector machines Computer vision image motion analysis Event detection Support Vector Network Videotapes image motion analysis abnormal event Eigenvector images computer vision Feature extraction video clips Nonnegative coding

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Short text classification based on LDA topic model

Short text classification based on LDA topic model

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International Conference on Audio, Language and image processing, ICALIP

作者： Qiuxing Chen Lixiu Yao Jie Yang Institution of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

ISBN: (纸本)9781509006557

As the rapid development of computer technology and network communication, short text data has increased enormously. Classifying the short text snippets is a great challenge to due to its less semantic information and high sparseness. In this paper, we proposed an improved short text classification method based on Latent Dirichlet Allocation topic model and K-Nearest Neighbor algorithm. The generated probabilistic topics help both make the texts more semantic-focused and reduce the sparseness. In addition, we present a novel topic similarity measure method with the topic-word matrix and the relationship of the discriminative terms between two short texts. A short text dataset for experiment validation is constructed by crawling the posts from Sina News website. The extensive and comparable experimental results obtained show the effectiveness of our proposed method.

关键词： Training Text categorization Resource management Probabilistic logic Semantics Classification algorithms Search engines

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Trajectory matching algorithm based on clustering and GPR in video retrieval

Communications in Computer and Information Science

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Communications in Computer and Information Science 2013年 355卷 373-381页

作者： Wang, Tianlu Zhang, Xianmin Department of Automation Shanghai Jiao Tong University Image Processing and Pattern Recognition Institution of Shanghai Jiao Tong University Shanghai 200240 China

This paper proposes an approach for trajectory matching in video retrieval. Algorithm is consist of three parts. First, a terse trajectory contains most important temporal and spatial characters are abstracted. Then, abstracted trajectories are classified into several classes by using reformed k-means cluster method according to their position and acceleration features. At the end, Gaussian Process regression model is built and trained using clustered trajectories and trajectories classes which are similar with the given retrieval targets are found out. Advantages of this algorithm include the possibility of generalized clustering for similar trajectories in different scales and partial trajectories matching. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Trajectories

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VIOLENT VIDEO DETECTION BASED ON MoSIFT FEATURE AND SPARSE CODING

VIOLENT VIDEO DETECTION BASED ON MoSIFT FEATURE AND SPARSE C...

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IEEE International Conference on Acoustics, Speech and Signal processing

作者： Long Xu Chen Gong Jie Yang Qiang Wu Lixiu Yao Institution of Image Processing and Pattern Recognition Shanghai Jiao Tong University China School of Computing and Communications University of Technology Sydney Australia

ISBN: (纸本)9781479928941

To detect violence in a video, a common video description method is to apply local spatio-temporal description on the query video. Then, the low-level description is further summarized onto the high-level feature based on Bag-of-Words (BoW) model. However, traditional spatio-temporal descriptors are not discriminative enough. Moreover, BoW model roughly assigns each feature vector to only one visual word, therefore inevitably causing quantization error. To tackle the constrains, this paper employs Motion SIFT (MoSIFT) algorithm to extract the low-level description of a query video. To eliminate the feature noise, Kernel Density Estimation (KDE) is exploited for feature selection on the MoSIFT descriptor. In order to obtain the highly discriminative video feature, this paper adopts sparse coding scheme to further process the selected MoSIFTs. Encouraging experimental results are obtained based on two challenging datasets which record both crowded scenes and non-crowded scenes.

关键词： Videotapes Eigenvector Quantization Feature extraction Violence BOW labeling scheme High-level features LOW LEVEL

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Automatic detection of mitral annulus in echocardiography based on prior knowledge and local context

Automatic detection of mitral annulus in echocardiography ba...

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Computers in Cardiology (CinC)

作者： Wei Song Wei Xu Xin Yang Liping Yao Kun Sun Shanghai Jiao Tong University Shanghai China Institution of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Xinhua Hospital School of Medicine Shanghai China

ISBN: (纸本)9781479908851

Due to the inherent noisy, low resolution and limited imaging range of echocardiography, it is difficult to identify mitral annulus (MA) where valves end that is crucial for further segmentation, modeling and multi-modalities registration of mitral valves. This work aims to automatically detect MA hinge points combining information of intra-cardiac local context and location relationships. The method includes the following steps: (1) segment left ventricle (LV) by prior shape and local histogram fitting based Active Contour Model (ACM); (2) design the local context features for training and classification of MA hinge points; (3) utilize additive min kernel based Support Vector Machines (SVM) classifier for fast computation to obtain MA candidates; (4) estimate MA hinge points by K-means algorithm under the location constraint of LV and MA. Our method was tested on echocardiographic four chamber image sequence of 10 pediatric patients (6 boys, 4 girls, 7.6±3.4 years). Compared with the manual annotations, the automatically detected MA results are reliable with reasonable accuracy, for lateral point (2.0±1.9, 1.8±1.2) pixels and for septal point (2.9±2.6, 1.2±1.0) pixels.

关键词： Mathematical model Fasteners Additives Histograms Kernel Support vector machines Equations

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