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第35届中国控制会议

作者： Penglin LI Yue LIU Yadong ZHAO Jie YANG Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University State Key Laboratory of Industrial Control Technology Institute of Industrial Process ControlCollege of Control Science and EngineeringZhejiang University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (纸本)9781509009107

In this paper,we discuss consensus problems for antagonistic networks with double integrator *** cases are analyzed:(1) undirected graphs with fixed topology on antagonistic networks;(2) undirected graphs with fixed topology and time-delay on antagonistic *** both cases,distributed consensus protocols are proposed,with sufficient and necessary conditions *** is proved that the largest tolerable time-delay is only related to the largest eigenvalue of the graph ***,simulations are provided to demonstrate the obtained theoretical results.

关键词： Consensus Fixed Topology Multi-agent Antagonistic Networks Time-delay

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A novel fast full frame video stabilization via three-layer model 21

A novel fast full frame video stabilization via three-layer ...

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21st International Conference on MultiMedia Modeling, MMM 2015

作者： Long, Wei Yang, Jie Song, Dacheng Chen, Xiaogang He, Xiangjian Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China University of Shanghai for Science and Technology Shanghai China School of Computing and Communications University of Technology Sydney Australia

ISBN: (纸本)9783319144443

Video stabilization is an important video enhancement technology which aims at removing undesired shaking from input videos. A challenging task in stabilization is to inpaint the missing pixels of undefined areas in the motion-compensated frames. This paper describes a new video stabilization method. It adopts a multi-layer model to improve the efficiency of the video stabilization. The undefined areas can be inpainted in real-time. Compared with traditional methods, our proposed algorithm only need maintain a single updated mosaic image for video completion, while previous methods require to store all neighboring frames and then registered with the current frame. The experimental results demonstrated the effectiveness of the proposed approach. © Springer International Publishing Switzerland 2015.

关键词： Motion compensation

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A nearest neighbor search method for image matching based on ORB

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Journal of Information and Computational Science 2015年第7期12卷 2691-2700页

作者： Zou, Jiancheng Wang, Xiaofei Institute of Image Processing and Pattern Recognition North China University of Technology Beijing China

ORB algorithm is one of the widely used local image feature matching methods. In order to increase the speed of ORB matching, this paper uses a Nearest Neighbor (NN) search method to replace the Hamming distance and proposes a Nearest Neighbor search method for image matching based on ORB. Firstly, the image feature points are detected by FAST and then the corners orientations are determined. Meanwhile, the corresponding binary descriptors with BRIEF are obtained. Finally the feature points can be matched by finding the nearest Euclidean distances. Experimental results show that the new algorithm significantly enhances the matching speed. Copyright © 2015 Binary Information Press.

关键词： image matching

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Small target detection using an optimization-based filter 40

Small target detection using an optimization-based filter

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

作者： Xie, Kai Fu, Keren Zhou, Tao Yang, Jie Wu, Qiang He, Xiangjian Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China School of Computing and Communications University of Technology Sydney Australia

ISBN: (纸本)9781467369978

Small target detection is a critical problem in the Infrared Search And Track (IRST) system. Although it has been studied for years, there are some challenges remained, e.g. cloud edges and horizontal lines are likely to cause false alarms. This paper proposes a novel method using an optimization-based filter to detect infrared small target in heavy clutter. First, we design a certain pixel area as active area. Second, a weighted quadratic cost function is performed in the active area. Finally, a filter based on statistics of active area is derived from the cost function. Our method could preserve heterogeneous area, meanwhile, remove target region. Experimental results show our method achieves satisfied performance in heavy clutter. © 2015 IEEE.

关键词： active area area statistics heavy clutter optimization-based filter small target detection

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Automated multi-contrast brain pathological area extraction from 2D MR images

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Journal of Applied Research and technology 2015年第1期13卷 58-69页

作者： Dvořák, P. Bartušek, K. Kropatsch, W.G. Smékal, Z. Institute of Scientific Instruments of the ASCR V.v.i Academy if Sciences of the Czech Republic Brno Czech Republic Dept. of Telecommunications Faculty of Electrical Engineering and Communication Brno University of Technology Brno Czech Republic Pattern Recognition and Image Processing Group Institute of Computer Graphics and Algorithms Faculty of Informatics Vienna University of Technology Vienna Austria

The aim of this work is to propose the fully automated pathological area extraction from multi-parametric 2D MR images of brain. The proposed method is based on multi-resolution symmetry analysis and automatic thresholding. The proposed algorithm first detects the presence of pathology and then starts its extraction. T2 images are used for the presence detection and the multi-contrast MRI is used for the extraction, concretely T2 and FLAIR images. The extraction is based on thresholding, where Otsu's algorithm is used for the automatic determination of the threshold. Since the method is based on symmetry, it works for both axial and coronal planes. In both these planes of healthy brain, the approximate left-right symmetry exists and it is used as the prior knowledge for searching the approximate pathology location. It is assumed that this area is not located symmetrically in both hemispheres, which is met in most cases. The detection algorithm was tested on 203 T2-weighted images and reached the true positive rate of 87.52% and true negative rate of 93.14%. The extraction algorithm was tested on 357 axial and 443 coronal real images from publicly available BRATS databases containing 3D volumes brain tumor patients. The results were evaluated by Dice Coefficient (axial: 0.85 ± 0.11, coronal 0.82 ± 0.18) and by Accuracy (axial: 0.96 ± 0.05, coronal 0.94 ± 0.09). © 2015 Universidad Nacional Autónoma de México.

关键词： Brain Pathology Brain Tumor MRI Multi-contrast MRI Symmetry Analysis

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SPARSE CODING-BASED SPATIOTEMPORAL SALIENCY FOR ACTION recognition

SPARSE CODING-BASED SPATIOTEMPORAL SALIENCY FOR ACTION RECOG...

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IEEE International Conference on image processing

作者： Tao Zhang Long Xu Jie Yang Pengfei Shi Wenjing Jia Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Faculty of Engineering and Information Technology University of Technology

ISBN: (纸本)9781479983407

In this paper, we address the problem of human action recognition by representing image sequences as a sparse collection of patch-level spatiotemporal events that are salient in both space and time domain. Our method uses a multi-scale volumetric representation of video and adaptively selects an optimal space-time scale under which the saliency of a patch is most significant. The input image sequences are first partitioned into non-overlapping patches. Then, each patch is represented by a vector of coefficients that can linearly reconstruct the patch from a learned dictionary of basis patches. We propose to measure the spatiotemporal saliency of patches using Shannon's self-information entropy, where a patch's saliency is determined by information variation in the contents of the patch's spatiotemporal neighborhood. Experimental results on two benchmark datasets demonstrate the effectiveness of our proposed method.

关键词： Sparse coding Spatiotemporal saliency Action recognition Shannon information entropy Sparse coding image sequences Shannon information Patches

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A Hybrid image Feature Descriptor for Classification

A Hybrid Image Feature Descriptor for Classification

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International Conference on Computational Intelligence and Security

作者： Hassan Dawood Hussian Dawood Ping Guo Image Processing and pattern Recognition Laboratory Beijing Normal University Beijing China Department of Computer Engineering University of Engineering and Technology Taxila Pakistan Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

Feature extraction methods have an important role in image classification. In this paper, a hybrid texture feature descriptor is proposed by utilizing the attributes of two complementary features, PRICoLBP and LPQ. PRICoLBP performs well in the case of geometric and photometric variations however it does not properly express the local texture of an image, while LPQ method performs well for the local structure of an image. We propose to use the hybrid scheme by combining the properties of PRICoLBP and LPQ and name it as Pair wise Rotation Invariant Co-occurrence Local Phase Quantization (PRICLPQ). Standard texture and material datasets have been used to verify the robustness of proposed hybrid scheme. The experiments show that the proposed hybrid scheme outperforms the state-of-the-art feature extraction methods like LBP, LPQ, CLBP, LBPV, SIFT, MSLBP, Lazebnik and PRICoLBP in term of accuracy.

关键词： Feature extraction Histograms Robustness Training Quantization (signal) Support vector machines Yttrium

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SALIENT OBJECT DETECTION USING NORMALIZED CUT AND GEODESICS

SALIENT OBJECT DETECTION USING NORMALIZED CUT AND GEODESICS

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IEEE International Conference on image processing

作者： Keren Fu Chen Gong Irene Y. H. Gu Jie Yang Pengfei Shi Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Department of Signals and Systems Chalmers University of Technology

ISBN: (纸本)9781479983407

Recently the Normalized cut (Ncut) has been introduced to salient object detection [1, 2]. In this paper we validate that instead of proposing new detection models that leverage the Ncut, the previous geodesic saliency detection model which computes shortest paths on a graph can be adapted to eigenvectors of the Ncut to produce superior performance. Since the Ncut partitions a graph in a normalized energy minimization fashion, resulting eigenvectors contain decent cluster information that can group visual contents. Combining it with the existing geodesic saliency detection is conducive to highlighting salient objects uniformly, yielding to improved detection accuracy. Experiments by comparing with 12 existing methods on four benchmark datasets show the proposed method significantly outperforms the original geodesic saliency model and achieves comparable performance to state-of-the-art methods.

关键词： Salient object detection Normalized cut Geodesic saliency Saliency map Geodesic Object detection Eigenvector Line graph

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Visual Tracking via Nonnegative Regularization Multiple Locality Coding

Visual Tracking via Nonnegative Regularization Multiple Loca...

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International Conference on Computer Vision Workshops (ICCV Workshops)

作者： Fanghui Liu Tao Zhou Jie Yang Irene Y. H. Gu Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Dept. of Signals and Systems Chalmers University of Technology

ISBN: (纸本)9781467397124

This paper presents a novel object tracking method based on approximated Locality-constrained Linear Coding (LLC). Rather than using a non-negativity constraint on encoding coefficients to guarantee these elements nonnegative, in this paper, the non-negativity constraint is substituted for a conventional l2 norm regularization term in approximated LLC to obtain the similar nonnegative effect. And we provide a detailed and adequate explanation in theoretical analysis to clarify the rationality of this replacement. Instead of specifying fixed K nearest neighbors to construct the local dictionary, a series of different dictionaries with pre-defined numbers of nearest neighbors are selected. Weights of these various dictionaries are also learned from approximated LLC in the similar framework. In order to alleviate tracking drifts, we propose a simple and efficient occlusion detection method. The occlusion detection criterion mainly depends on whether negative templates are selected to represent the severe occluded target. Both qualitative and quantitative evaluations on several challenging sequences show that the proposed tracking algorithm achieves favorable performance compared with other state-of-the-art methods.

关键词： Dictionaries Encoding Target tracking Visualization Bismuth image reconstruction image coding

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An image fusion method of multi-scale image based on HMM and genetic algorithms

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Journal of Computational Information Systems 2015年第12期11卷 4367-4374页

作者： Jiang, Zetao Wu, Donghui The Institute of Computer Science and Engineering Guilin University of Electronic Technology Guilin China The Key Lab of Image Processing and Pattern Recognition of Jiangxi Province Nanchang Hangkong University Nanchang China

At present, in the field of pixel-level image fusion, researchers tend to treat each pixel independently, which destroys the relationship between the images to be fused. In view of this defects, this paper aims to propose a method for multi-scale image fusion based on Genetic Algorithm (GA) under the guidance of Hidden Markov Model (HMM). This fusion method is set on the following principles. First of all, the wavelet transformation (WT) of the two images to be fused will be conducted. And then establish HMM for the fusion coefficients from high to low in descending hierarchical order. Finally, guided by HMM, the author applies GA to searching hierarchically for the optimal fusion coefficient. With this method, the best fusion effect will be achieved. This method take good advantage of the correlation information between the images to be fused so as to improve the fidelity and accuracy of the fusion. Given this, the author makes an empirical analysis on this fusion method, which proves to be feasible and effective. ©, 2015, Binary Information Press. All right reserved.

关键词： Genetic algorithms

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