检索结果-内蒙古大学图书馆

第三十三届中国控制会议

作者： YANG Yawen ZHANG Peng Peng QIAO Yu YANG Jie WANG Sheng Zheng The Key Laboratory of Ministry of Education for System Control and Information Processing Institute of Image Processing and Pattern RecognitionShanghai Jiao Tong University Merchant Marine College Shanghai Maritime University

ISBN: (纸本)9781479947249

Point matching is an important component of image *** years,Coherent Point Drift(CPD) method becomes a very popular point matching *** treats point matching as a probability estimation problem and speeds up the process of matching a *** this method,one set of points are thought to be sampled from a Gaussian Mixture Model(GMM),which is centered by the other set of ***,CPD is sensitive to outliers and noises,especially when the noise ratio increased or the number of outliers gets much *** deal with this problem,we introduce shape context into the step of searching for matching points and then improve the form of prior probabilities of GMM in this *** main idea of our method is that if the most points in a data set are likely to be matched to a particular centroid,this Gaussian component should be have a more influence to ***,we set prior probability of GMM with the similarity between GMM components and the data *** the computation of similarity is based on shape *** experiments on 2D and 3D images show that when noise ratio is low,our method performs as well as CPD does,but as the ratio increased,our method is more robust and satisfactory than CPD.

关键词： CPD,Shape context,image registration,Point matching

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Visual tracking based on weighted subspace reconstruction error

Visual tracking based on weighted subspace reconstruction er...

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作者： Zhou, Tao Zhang, Junhao Xie, Kai Yang, Jie He, Xiangjian Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Faculty of Engineering and Information Technology University of Technology Sydney Australia

ISBN: (纸本)9781479957514

It is a challenging task to develop an effective and robust visual tracking method due to factors such as pose variation, illumination change, occlusion, and motion blur. In this paper, a novel tracking algorithm based on weighted subspace reconstruction error is proposed. We first compute the discriminative weights by sparse construction error with template dictionary consisted of positive and negative samples, and then confidence map for candidates is computed through subspace reconstruction error. Finally, the location of the target object is estimated by maximizing the decision map which is combined discriminative weights and subspace reconstruction error. Furthermore, we use the new evaluation criterion to verify the robustness of the current tracking result, which can reduce the accumulated error effectively. Experimental results on some challenging video sequences show that the proposed algorithm performs favorably against seven state-of-the-art methods in terms of accuracy and robustness. © 2014 IEEE.

关键词： Errors

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Online learning of multi-feature weights for robust object tracking

Online learning of multi-feature weights for robust object t...

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IEEE International Conference on image processing

作者： Tao Zhou Harish Bhaskar Kai Xie Jie Yang Xiangjian He Pengfei Shi Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Dept. of Elec. & Comp. Engg. Khalifa Univ. of Science Technology and Research Abu Dhabi U.A.E Faculty of Engineering and Information Technology University of Technology Sydney Australia

Sparse Representation based Classification (SRC) and its potential in object tracking have been explored in recent years. However, the trade-off between the discriminative ability of the overly emphasized sparse representation and the lack of insight on correlation of visual information has raised questions over the general applicability of such methods in object tracking. In addition, the need for the optimization of a series of l 1 -regularized least square norm, increases the computational complexity thereby limiting their usage in real-time applications. In this paper, a novel approach to robust object tracking is proposed. First, the variations in the appearance of the tracked target is modelled using PCA basis vectors, and further, a l 2 -regularized least square method is used to solve the proposed representation model. In order to improve the robustness of feature representation in object tracking applications, weights are associated with multiple trackers; each formulated using a different feature, and adapted via an online learning scheme. Finally, a decision fusion criterion is imposed to generate an optimized output through the weighted combination of different tracking results. Experiments on challenging video sequences have demonstrated the superior accuracy and robustness of the proposed method in comparison to thirteen other state-of-the-art baselines.

关键词： Target tracking Robustness Object tracking Lighting Clutter Computed tomography Visualization

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Part-Based Tracking with Appearance Learning and Structural Constrains

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8834卷 594-601页

作者： Xiang, Wei Zhou, Yue Institute of Image Processing and Pattern Recognition Jiao Tong University Shanghai China

Adaptive tracking-by-detection methods are widely used in computer vision for tracking objects. Despite these methods achieve promising results, deformable targets and partial occlusions continue to represent key problem in visual tracking. In this paper, we propose a part-based visual tracking method. First, we take advantage of the existing online learning appearance model to learning the appearance of each part. Second, we propose a novel part initialization method and an affine invariant structural constrain between these parts. Third, a tracking model based on the appearance of each part and the spatial relationship between the parts is proposed. We make use of an optimization algorithm to find the best parts during tracking, update the appearance model and the structural constraints between parts simultaneously. In this paper we show our method has many advantages over the pure appearance learning based tracking model. Our method can effective solve the partial occlusion problem, and relieve the drift problems. What’s more, our method achieves great result while tracking the target of which geometric appearance changes drastically over time. © Springer International Publishing Switzerland 2014.

关键词： Target tracking

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A Robust Method for High-Accuracy Microbe Identification Based on image processing

A Robust Method for High-Accuracy Microbe Identification Bas...

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2014 IEEE International Conference on Progress in Informatics and Computing

作者： Mingqi Cao Yuncai Liu Shanghai JiaoTong University Institute of Image Processing and Pattern Recognition

We present a novel fast method based on computer vision toidentify microbe. The proposed method is simple but absolutely effective. It combines approximate parallel light source and industrial camera, toautomatically accomplish the bacteria identification and monitor the growing states of bacteria during the progress of a drug sensitive test. Based on this method, the color information and turbidity information, which reflect the primary information of drug sensitive tests, can be obtained fast, while processing efficiency can be as high as hundreds of milliseconds per frame. The performance of our method is significantly accurate and robust.

关键词： microbe identification drug sensitive test localization color feature turbidity feature

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Accurate Computation of Fingerprint Intrinsic images with PDE-Based Regularization

Accurate Computation of Fingerprint Intrinsic Images with PD...

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7th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2012

作者： Li, Mingyan Chen, Xiaoguang College of Sciences Beijing Forestry University 100083 Beijing China Institute of Image Processing and Pattern Recognition College of Sciences North China University of Technology 100083 Beijing China

The intrinsic images of fingerprint, such as orientation field and frequency map, represent the particular and basic characteristics of fingerprint ridge/valley patterns, and play a key role in feature extraction and matching of the fingerprint recognition system. In this paper, a novel algorithm is presented for accurate computation of fingerprint intrinsic images with PDE-based regularization technique. First, the coarse orientation field is estimated using general gradient-based method, and the frequency map is estimated by Fourier spectrum analysis of the projected curve of local window. Then, to measure the reliability of the intrinsic images, the quality map is computed based on the gray-scale intensity and local structural information. Finally, accurate orientation field and frequency map are reconstructed with PDE-based regularization of nonlinear diffusion filtering which is controlled by the quality-based diffusivity. Experimental results illustrated the efficiency of the proposed approach. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Spectrum analysis

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Joint probabilistic constrained robust beamforming and antenna selection

Joint probabilistic constrained robust beamforming and anten...

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IEEE International Conference on Signal processing, Communications and Computing (ICSPCC)

作者： Jinwang Yue Yong Jin Zhentao Hu Xianxing Liu Institute of Image Processing & Pattern Recognition Henan University Kaifeng China

We propose a novel method for joint probabilistic constrained robust beamforming and antenna selection used in cognitive radio (CR) networks. Assuming complex Gaussian distributed channel state information (CSI) errors, the Bernstein-type inequalities are used to transform the no closed-form probabilistic constrained into the deterministic forms. Moreover, l1-norm is introduced as the closest convex approximation of ℓ0-norm. So, the original NP-hard optimal problem can be relaxed to as a tractable convex optimization problem. A computationally efficient and near-optimal solution is obtained by a iteratively re-weighted algorithm. Simulations show that the proposed algorithm meet prescribed service levels at a relatively small excess transmission power in a number of transmitter reduction scenarios.

关键词： Array signal processing Interference Probabilistic logic Antennas Signal to noise ratio Robustness Vectors

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SALIENCY DETECTION VIA FOREGROUND RENDERING AND BACKGROUND EXCLUSION

SALIENCY DETECTION VIA FOREGROUND RENDERING AND BACKGROUND E...

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IEEE International Conference on image processing

作者： Yijun Li Keren Fu Lei Zhou Yu Qiao Jie Yang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University

ISBN: (纸本)9781479957521

In this paper, a novel approach for image visual saliency detection is proposed from both the salient object (foreground) and the background perspective. To better highlight the salient object, we start from what is a salient object and adopt priors including contrast prior and center prior to measure the dissimilarity between different image elements. To better suppress the background, we focus on what is the background and measure the pixel-wise saliency by the minimum seam cost where the seam is an optimal 8-connected path from the pixel to some boundary pixel. The final saliency map is obtained by the combination of two measure systems which leads to the goal of both highlighting the salient object and suppressing the background. Both qualitative and quantitative experiments conducted on a benchmark dataset show that our approach outperforms seven state-of-the-art methods.

关键词： Saliency detection SODM map BDM map Saliency map

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Repetitive shapes detection using affine invariant constraints

Repetitive shapes detection using affine invariant constrain...

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2014 International Conference on Communication Technology and Application(CTA2014)

作者： Z.H.Yang P.Dong Institute of Image Processing & Pattern Recognition North China University of Technology

ISBN: (纸本)9781845649302

This paper presents a novel approach for finding more accurate feature pairs which is not only invariant to affine transformation, but also deals with images with repetitive shapes. First, the more accurate and robust homographic transformation between different views could be calculated through bi-directional matching and appropriate selection of threshold. Second, an affine geometric property, ratios of areas of corresponding triangles are affine invariant, is used to obtain more feature pairs based on the first step. Experiments demonstrate that the proposed method outperforms the state-of-art ASIFT in the number of correct feature pairs and matching accuracy among images with repetitive patterns.

关键词： image matching repetitive shapes feature points affine invariance ASIFT

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recognition by detection: Perceiving human motion through part-configured feature maps

Recognition by detection: Perceiving human motion through pa...

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IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

作者： Lei Wang Jun Wu Zhimin Zhou Yuncai Liu Xu Zhao Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition

Visually perceiving human motion at semantic level is an important however challenging problem in multimedia area. In this work, we propose a novel approach to map the low-level responses from visual detection to semantically sensitive description to human actions. The feature map is triggered by the output of deformable part model detection, in which the critical information about body parts configuration is contained implicitly under the specific human actions. We map the filter responses of the detectors to an effective feature description, which encodes the position and appearance information of the root and every body parts simultaneously. Statistically, the obtained feature map captures the significance of relative configuration of body parts, therefore is robust to the false detections occurred in the individual part detectors. We conduct comprehensive experiments and the results show that the method generates discriminative action features and achieves remarkable performance in most of the cases.

关键词： Accuracy Feature extraction YouTube Vectors Detectors Visualization Deformable models

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