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IEEE International Conference on Multimedia and Expo (ICME)

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

In this paper, a novel and robust tracking method based on efficient manifold ranking is proposed. For tracking, tracked results are taken as labeled nodes while candidate samples are taken as unlabeled nodes, and the goal of tracking is to search the unlabeled sample that is the most relevant with existing labeled nodes by manifold ranking algorithm. Meanwhile, we adopt non-adaptive random projections to preserve the structure of original image space, and a very sparse measurement matrix is used to efficiently extract low-dimensional compressive features for object representation. Furthermore, spatial context is used to improve the robustness to appearance variations. Experimental results on some challenging video sequences show the proposed algorithm outperforms six state-of-the-art methods in terms of accuracy and robustness.

关键词： Target tracking Manifolds Context Computational modeling Robustness Clutter

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Objective measurement of image degradation caused by optical transmission effects

Objective measurement of image degradation caused by optical...

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International Conference on Systems and Informatics (ICSAI)

作者： Ming Li Jie Yang School of Electronics and Information Shanghai Dianji University Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9781479954599

An objective approach is proposed to measure the image degradation caused by optical transmission effects of atmospheric turbulence. Comparisons of the proposed measure with existing objective image quality measures are performed and the correlations between the measure and subjective ratings are quantified. Experiments on wind-tunnel images and simulated turbulence-degraded images produce good results. The proposed measure may serve as a complement to state-of-the-art measures in evaluating image degradation caused by turbulence. It can also be applied as a criterion for frame selection and iteration termination for iterative restoration algorithms or help evaluate the performances of image restoration algorithms.

关键词： Optical imaging Optical variables measurement Manganese image quality Adaptive optics Degradation Optical attenuators

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A RIF based mapping of RDB2RDF

International Journal of Database Theory and Application

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International Journal of Database Theory and Application 2014年第6期7卷 29-44页

作者： Chen, Ying Xu, Zhuoming Ni, Yuyan Cao, Guangxu Zhang, Shiqing College of Computer and Information Hohai University Nanjing Jiangsu China Institute of Image Processing and Pattern Recognition Taizhou University Taizhou Zhejiang China

Mapping RDB to RDF (i.e., RDB2RDF) is the key to constructing the Semantic Web, hence has been an active research field during the last decade. Many technically heterogeneous RDB2RDF tools resulted in non-interchangeable and unreusable RDB2RDF mapping descriptions. In 2009, the W3C RDB2RDF Incubator Group Report once strongly suggested that the RDB2RDF mapping language be expressed in rules as defined by the W3C Rule Interchange Format (RIF) Working Group, because rules are an effective way to express mappings between information models, and RIF, as part of the infrastructure for the Semantic Web, is now a standard for exchanging rules among Web rule systems. This paper addresses the issue of RIF-based RDB2RDF mapping and proposes a database semantics-driven, RIF Production Rule Dialect (RIF-PRD) based mapping description approach. The work includes defining a set of generic RIF-PRD mapping rules for RDB2RDF, developing a prototype mapping engine called RIFD2RME (stands for RIF-based RDB2RDF Mapping Engine), and conducting case study experiments with the prototype. The experimental results indicate that the proposed mapping approach is achievable and effective.

关键词： Mapping

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Adaptive regularization deconvolution extraction algorithm for spectral signal processing

Adaptive regularization deconvolution extraction algorithm f...

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IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA)

作者： Jian Yu Ping Guo A-li Luo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China National Astronomical Observatories Chinese Academy of Sciences Beijing China

Deconvolution is known as an ill-posed problem. In order to solve such a problem, a regularization method is needed to constrain the solution space and find a plausible and stable solution. In practice, it is very computation intensive when using cross-validation method to select the regularization parameter. In this paper, we present an adaptive regularization method to find the optimal regularization parameter value and represent the trade-off between model fitness of the data and the smoothness of the extracted signal. Spectral signal extraction experimental results demonstrate that the time complexity the proposed method is much lower than the one without adaptive regularization and is convenient for users also. And quantitative performance analysis show that the proposed intelligent approach performs better than that of current deconvolution extraction method and other extraction method used in the Large Area Multi-Objects Fiber Spectroscopy Telescope spectral signal processing pipeline.

关键词： Deconvolution Charge coupled devices Equations Apertures Convolution Mathematical model Sparse matrices

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EFFECTIVE SMALL DIM TARGET DETECTION BY LOCAL CONNECTEDNESS CONSTRAINT

EFFECTIVE SMALL DIM TARGET DETECTION BY LOCAL CONNECTEDNESS ...

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IEEE International Conference on Acoustics, Speech and Signal processing

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

ISBN: (纸本)9781479928941

The main drawback of conventional filtering based methods for small dim target (SDT) detection is they could not guarantee sufficient suppression ability towards trivial high frequency component which belongs to background, such as strong corners and edges. To overcome this bottleneck, this paper proposes an effective SDT detection algorithm by using local connectedness constraint. Our method provides direct control for target size, ensure high accuracy and could be easily embedded into the classical sliding-window based framework. The effectiveness of the proposed method is validated using images with cluttered background.

关键词： Object detection Direct control clutter background images sliding windows Detection algorithms BACKGROUND

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Visual tracking based on weighted subspace reconstruction error

Visual tracking based on weighted subspace reconstruction er...

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IEEE International Conference on image processing

作者： Tao Zhou Junhao Zhang Kai Xie Jie Yang Xiangjian He 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)9781479957521

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.

关键词： Target tracking Dictionaries Robustness image reconstruction Visualization Computer vision

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Automatic image annotation exploiting textual and visual saliency

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 8836卷 95-102页

作者： Gu, Yun Xue, Haoyang Yang, Jie Jia, Zhenhong Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China School of Information Science and Engineering Xinjiang University Urumqi China

Automatic image annotation is an attractive service for users and administrators of online photo sharing websites. In this paper, we propose an image annotation approach exploiting visual and textual saliency. For textual saliency, a concept graph is firstly established based on the association between the labels. Then semantic communities and latent textual saliency are detected;For visual saliency, we adopt a dual-layer BoW (DL-BoW) model integrated with the local features and salient regions of the image. Experiments on NUS-WIDE dataset demonstrate that the proposed method outperforms other state-of-the-art approaches. © Springer International Publishing Switzerland 2014.

关键词： image annotation

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VISUAL OBJECT TRACKING WITH ONLINE LEARNING ON RIEMANNIAN MANIFOLDS BY ONE-CLASS SUPPORT VECTOR MACHINES

VISUAL OBJECT TRACKING WITH ONLINE LEARNING ON RIEMANNIAN MA...

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IEEE International Conference on image processing

作者： Yixiao Yun Keren Fu Irene Yu-Hua Gu Jie Yang Dept. of Signals and Systems Chalmers Univ. of Technology Inst. of Image Processing & Pattern Recognition Shanghai Jiao Tong Univ.

ISBN: (纸本)9781479957521

This paper addresses issues in video object tracking. We propose a novel method where tracking is regarded as a one-class classification problem of domain-shift objects. The proposed tracker is inspired by the fact that the positive samples can be bounded by a closed hypersphere generated by one-class support vector machines (SVM), leading to a solution for robust learning of target model online. The main novelties of the paper include: (a) represent the target model by a set of positive samples as a cluster of points on Riemannian manifolds;(b) perform online learning of target model as a dynamic cluster of points flowing on the manifold, in an alternate manner with tracking;(c) formulate geodesic-based kernel function for one-class SVM on Riemannian manifolds under the log-Euclidean metric. Experiments are conducted on several videos, results have provided support to the proposed method.

关键词： Visual object tracking Support vector machines One-class classification Online learning Riemannian manifold Covariance matrix

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3-D centerline extraction for virtual cardiovascular endoscopy

3-D centerline extraction for virtual cardiovascular endosco...

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International Conference on Wavelet Active Media Technology and Information processing (ICWAMTIP)

作者： Jing Li Xin Yang Li Ping Yao Kun Sun Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Xinhua Hospital Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781479972098

This paper discusses centerline extraction algorithms for virtual cardiovascular endoscopy system. A fully automatic extraction method is proposed which is significantly enhanced from current distance mapping method. The new approach consists of four steps: preprocessing; construction of improved Distance From Boundary field; centerline extraction; mean value smoothing of centerline. Based on the proposed automatic approach, an interactive extraction method is presented in which a centerline connects specified points selected by cardiologists. This interactive approach makes the viewport closer to pathological changes in the aorta and human heart, so cardiologists can observe focuses more clearly. The two algorithms have been applied to the virtual cardiovascular endoscopy system, and the experiments prove that our methods work well in the process of auxiliary diagnosis.

关键词： Endoscopes Heart Navigation Computed tomography Biomedical imaging Smoothing methods Cavity resonators

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Text-independent writer identification by feature fusion

Text-independent writer identification by feature fusion

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International Conference on Intelligent Control and Information processing (ICICIP)

作者： Yongjie Hu Wenming Yang Youbin Chen Department of Electronic Engineering of Tsinghua University Zhejiang University Research interests include digital image processing and computer vision Department of Electronic Engineering of Tsinghua University Research interests include digital image processing and pattern recognition

ISBN: (纸本)9781479936519

This paper explores text-independent writer identification by combining Bag of Features (BoF), contour-hinge and SIFT scales feature. The BoF method adopted differs from the common BoF approach for writer identification in that it extracts SIFT descriptors and uses Locality-constrained Linear Coding to get feature vector of each document. The Locality-constrained Linear Coding (LLC) tries to reconstruct each feature through locality constraint and has much more discriminative power than the common used Vector Quantization (VQ). Contour-hinge feature can capture orientation and curvature of the ink trace. Modification is made to the original contour-hinge to improve the identification rate. Besides, we also use SIFT scale information and integrate these three kinds of features together. Experiments are conducted the challenging ICDAR2013 writer identification contest dataset and dataset for "ICFHR2012 Writer Identification Contest, Challenge 1: Latin Documents". The experiment results show that the proposed BoF approach outperforms the common ones that adopt VQ, and after the integration, our method achieves the best result on the entire ICDAR2013 and ICFHR2012 dataset under soft evaluation.

关键词： Feature extraction Vectors Encoding image reconstruction Text analysis Educational institutions

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