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作者： Yun, Yixiao Fu, Keren Gu, Irene Yu-Hua Yang, Jie Dept. of Signals and Systems Chalmers Univ. of Technology Gothenburg41296 Sweden Inst. of Image Processing and Pattern Recognition Shanghai Jiao Tong Univ. Shanghai200240 China

ISBN: (纸本)9781479957514

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. © 2014 IEEE.

关键词： Support vector machines

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3D deformable surfaces with locally self-adjusting parameters - A robust method to determine cell nucleus shapes

3D deformable surfaces with locally self-adjusting parameter...

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International Conference on pattern recognition

作者： Keuper, Margret Schmidt, Thorsten Padeken, Jan Heun, Patrick Palme, Klaus Burkhardt, Hans Ronneberger, Olaf Pattern Recognition and Image Processing Computer Science Department Freiburg University Germany Max-Planck Institute of Immunobiology Freiburg Germany University of Freiburg Germany Inst. of Biology II Freiburg Inst. for Advanced Studies - FRIAS University of Freiburg Germany

ISBN: (纸本)9780769541099

When using deformable models for the segmentation of biological data, the choice of the best weighting parameters for the internal and external forces is crucial. Especially when dealing with 3D fluorescence microscopic data and cells within dense tissue, object boundaries are sometimes not visible. In these cases, one weighting parameter set for the whole contour is not desirable. We are presenting a method for the dynamic adjustment of the weighting parameters, that is only depending on the underlying data and does not need any prior information. The method is especially apt to handle blurred, noisy, and deficient data, as it is often the case in biological microscopy. © 2010 IEEE.

关键词： Deformation

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Car plate detection using cascaded tree-style learner based on hybrid object features

Car plate detection using cascaded tree-style learner based ...

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IEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006

作者： Wu, Qiang Zhang, Huaifeng Jia, Wenjing He, Xiangjian Yang, Jie Hintz, Tom Computer Vision Research Group University of Technology Sydney PO Box 123 Broadway NSW 2007 Australia Inst. of Image Process. and Pattern Recognition Shanghai Jiaotong Univ. China

ISBN: (纸本)0769526888

Car plate detection is a key component in automatic license plate recognition system. This paper adopts an enhanced cascaded tree style learner framework for car plate detection using the hybrid object features including the simple statistical features and Harr-like features. The statistical features are useful for simplifying the process on cascade classifier. The cascaded tree-style detector design will further reduce the false alarm and the false dismissal while retaining a high detection ratio. The experimental results obtained by the proposed algorithm exhibit the encouraging performance. © 2006 IEEE.

关键词： Object recognition

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Low complexity reconfigurable architecture for the 5/3 and 9/7 discrete wavelet transform

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Journal of Systems Engineering and Electronics 2006年第2期17卷 303-308页

作者： Xiong Cheng yi Tian Jinwen Liu Jian Coll. of Electronic Information Engineering South Center Univ. for Nationalities Wuhan 430074 P.R. China Inst. of Pattern Recognition & Artificial Intelligence Key Lab. of Education Ministry for Image Processing and Intelligent Control Huazhong Univ. of Science & Technology Wuhan 430074 P.R. China

Efficient reconfigurable VLSI architecture for 1-D 5/3 and 9/7 wavelet transforms adopted in JPEG2000 proposal, based on lifting scheme is proposed. The embedded decimation technique based on fold and time multiplexing, as well as embedded boundary data extension technique, is adopted to optimize the design of the architecture. These reduce significantly the required numbers of the multipliers, adders and registers, as well as the amount of accessing external memory, and lead to decrease efficiently the hardware cost and power consumption of the design. The architecture is designed to generate an output per clock cycle, and the detailed component and the approximation of the input signal are available alternately. Experimental simulation and comparison results are presented, which demonstrate that the proposed architecture has lower hardware complexity, thus it is adapted for embedded applications. The presented architecture is simple, regular and scalable, and well suited for VLSI implementation.

关键词： VLSI discrete wavelet transform lifting scheme embedded decimation reeonfigurable.

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Fitting of a Closed Planar Curve Representing a Profile of an Archaeological Fragment 01

Fitting of a Closed Planar Curve Representing a Profile of a...

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proceedings VAST 2001 Virtual Reality, Archeology, and Cultural Heritage

作者： Hlavackova-Schindler, Kateřina Kampel, Martin Sablatnig, Robert Pattern Recog./Image Proc. Group Inst. of Computer Aided Automation Vienna University of Technology Favoritenstraße 9/1832 A-1040 Vienna Austria

ISBN: (纸本)1581134479

Motivated by the requirements of the present archaeology, we are developing an automated system for archaeological classification of ceramics. The basis for classification and reconstruction of ceramics is the profile, which is the cross-section of the fragment in the direction of the rotational axis of symmetry, and can be represented by a closed curve in the plane. This paper compares and combines several methods for interpolation and approximation of a closed curve by B-splines in the plane. The closed curve, representing the profile, is divided into several parts for which the most accurate method is selected. All the interpolation and approximation methods are compared on the provided data with respect to the achieved precision and 'complexity' of the curve description. The graphical output of the program suggests to the archaeologists, which combination of these methods gives the best representation of the reconstructed profile from the data under the smallest possible error and the simplest possible spline representation.

关键词： Ceramic materials

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Fingerprint preclassification using key-points

Fingerprint preclassification using key-points

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International Symposium on Speech, image processing and Neural Networks

作者： Ying Shan Peng Fei Shi Jie Gu Li Inst. of Image Process. & Pattern Recognition Shanghai Jiaotong Univ. China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)078031865X

A new idea of fingerprint preclassification named the key-point recognition method (KMF) is proposed which only pays attention to whether there is a general feature key-point in a certain area and takes no notice of what the feature is. Using this method, an automatic fingerprint recognition system has been developed, which is characterized by fewer requirements imposed on the preprocessing, lower sensitivity to the noise, higher capacity and parallelism being compared with other traditional ones. The system can list out the most promising fingerprints as a preclassifier.< >

关键词： Fingerprint recognition Equations Lattices Labeling Supervised learning Energy measurement Frequency measurement Brightness Convergence Hamming distance

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Layout and analysis: Finding text, titles, and photos in digital images of newspaper pages

Layout and analysis: Finding text, titles, and photos in dig...

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International Conference on Document Analysis and recognition

作者： J. Wieser A. Pinz Department for Pattern Recognition and Image Processing Inst. for Automation Technical University of of Vienna Wien Austria

An important step in the analysis of printed documents is the segmentation and classification of blocks into categories such as photographs, titles, paragraphs, etc. The authors present an approach to enhance and combine two commonly used methods, a merging bottom-up approach and a cutting top down approach, to segment pages of a newspaper. The implementation of a layout analysis system as a preprocessing module for a commercial product is described.< >

关键词： image analysis Digital images image segmentation Merging pattern analysis image converters Text analysis Optical character recognition software Particle separators Size measurement

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Human activity recognition in images using SVMs and geodesics on smooth manifolds 14

Human activity recognition in images using SVMs and geodesic...

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8th ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2014

作者： Yun, Yixiao Fu, Keren Gu, Irene Yu-Hua Aghajan, Hamid Yang, Jie Dept. of Signals and Systems Chalmers University of Technology Sweden Inst. of Image Processing and Pattern Recognition Shanghai Jiao Tong University China IMinds Ghent University Belgium AIR Lab. Stanford University United States

ISBN: (纸本)9781450329255

This paper addresses the problem of human activity recognition in still images. We propose a novel method that focuses on human-object interaction for feature representation of activities on Riemannian manifolds, and exploits underlying Riemannian geometry for classification. The main contributions of the paper include: (a) represent human activity by appearance features from local patches centered at hands containing interacting objects, and by structural features formed from the detected human skeleton containing the head, torso axis and hands;(b) formulate SVM kernel function based on geodesics on Riemannian manifolds under the log-Euclidean metric;(c) apply multi-class SVM classifier on the manifold under the one-against.all strategy. Experiments were conducted on a dataset containing 17196 images in 12 classes of activities from 4 subjects. Test results, evaluations, and comparisons with state-of-the-art methods provide support to the effectiveness of the proposed scheme. Copyright 2014 ACM.

关键词： Support vector machines

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Saliency Propagation from Simple to Difficult

Saliency Propagation from Simple to Difficult

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IEEE Conference on Computer Vision and pattern recognition

作者： Chen Gong Dacheng Tao Wei Liu S. J. Maybank Meng Fang Keren Fu Jie Yang Inst. of Image Process. & Pattern Recognition Shanghai Jiao Tong Univ. Shanghai China

ISBN: (纸本)9781467369657

Saliency propagation has been widely adopted for identifying the most attractive object in an image. The propagation sequence generated by existing saliency detection methods is governed by the spatial relationships of image regions, i.e., the saliency value is transmitted between two adjacent regions. However, for the inhomogeneous difficult adjacent regions, such a sequence may incur wrong propagations. In this paper, we attempt to manipulate the propagation sequence for optimizing the propagation quality. Intuitively, we postpone the propagations to difficult regions and meanwhile advance the propagations to less ambiguous simple regions. Inspired by the theoretical results in educational psychology, a novel propagation algorithm employing the teaching-to-learn and learning-to-teach strategies is proposed to explicitly improve the propagation quality. In the teaching-to-learn step, a teacher is designed to arrange the regions from simple to difficult and then assign the simplest regions to the learner. In the learning-to-teach step, the learner delivers its learning confidence to the teacher to assist the teacher to choose the subsequent simple regions. Due to the interactions between the teacher and learner, the uncertainty of original difficult regions is gradually reduced, yielding manifest salient objects with optimized background suppression. Extensive experimental results on benchmark saliency datasets demonstrate the superiority of the proposed algorithm over twelve representative saliency detectors.

关键词： Teachers region of an image propagation Propagation image invariant image dilation

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Small target detection using an optimization-based filter

Small target detection using an optimization-based filter

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IEEE International Conference on Acoustics, Speech and Signal processing

作者： K. Xie K. Fu T. Zhou J. Yang Q. Wu X. He Inst. of Image Process. & Pattern Recognition Shanghai Jiao Tong Univ. Shanghai China

ISBN: (纸本)9781467369985

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.

关键词： active area area statistics heavy clutter optimization-based filter small target detection Object detection useful area Filters Cost functions clutter

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