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International Conference on pattern recognition

作者： Xiaoyun Zhang Yuncai Liu Institute of Image Processing and Pattern Recognition ShangHai JiaoTong University Shanghai China

ISBN: (纸本)0769521282

An efficient point pattern matching algorithm for articulated and multiple objects is presented in this paper. A local to global strategy is adopted to get three layered matches starting from an initial partition of the point set using clustering method. Firstly, initial match with three point correspondences is obtained through local neighborhood and exhaustive search. Then, central match is expanded from initial match by alternating between next point matching and transformation update. Finally, ambiguous boundary points are matched and classified into their correspondent parts using the estimated alignment transformations, and missing or extra points are detected and rejected as outliers. Experiments on real images present satisfying results.

关键词： pattern matching pattern recognition Computer vision Layout Humans Tracking Joints image processing Clustering algorithms Partitioning algorithms

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Real time implementation of an MRF-based motion detection algorithm on a DSP board

Real time implementation of an MRF-based motion detection al...

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IEEE Digital Signal processing Workshop

作者： C. Dumontier F. Luthon J.P. Charras Image Processing and Pattern Recognition Laboratory National Polytechnical Institute Grenoble France

ISBN: (纸本)0780336291

The main concern in image processing is computation cost. Markov random fields (MRF) based algorithms particularly require a significant computation cost. Most of implementations of this kind of algorithms are made on parallel machines. This paper investigates an original solution for real time implementation of a robust MRF-based motion detection algorithm. A PC board, based on a pipeline architecture using a single powerfull DSP and FPGA components, is developed. The algorithm and the board are described. A processing rate of 15 images per second is achieved, showing the validity of this approach.

关键词： Motion detection Computational efficiency image processing Markov random fields Parallel machines Robustness Pipelines Computer architecture Digital signal processing Field programmable gate arrays

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Characteristic Line of Planar Homography Matrix and Its Applications in Camera Calibration

Characteristic Line of Planar Homography Matrix and Its Appl...

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International Conference on pattern recognition

作者： Jianhua Wang Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)0769525210

In this paper, we employ the concept of characteristic line to show some useful properties of planar homography matrix. These properties relate the characteristic line of a planar homography matrix with Euler angles of the planar pattern. Based on the characteristic line, a new method of linear camera calibration is proposed and a strategy to select poses of planar pattern during taking calibration images is suggested. This strategy can help ensure accuracy of calibration. Experiment results including both simulated data and real images validate the method and strategy

关键词： Transmission line matrix methods Cameras Calibration pattern recognition image processing Computational modeling Computer vision Layout Constraint theory Equations

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The role of context and model in urban aerial image interpretation focusing on buildings

The role of context and model in urban aerial image interpre...

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IEEE International Conference on Networking, Sensing and Control

作者： Jing Peng Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)0780381939

Guided by a building concept model, which interprets building into different levels and scales, this paper presents a method to extract buildings in monocular urban aerial images without priori illuminating or orientation knowledge. By using a shadow context model, a method was proposed to estimate the direction of shadow cast to verify the raw segmentations. Building extractions are refined by context, and a method of partial snake with the aid of the shadow cast direction is proposed, which can sharply reduce the iteration complexity and the influence caused by illumination. The extraction of self-shadow on gable roof with a proposed mathematical roof model is also discussed in this paper.

关键词： Context modeling Buildings Data mining image edge detection Urban areas Lighting Geographic Information Systems Radiometry image processing pattern recognition

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Matching based Highlight Removal

Matching based Highlight Removal

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International Conference on Multimedia Technology

作者： Yiren Xu Fujian Wang Yuming Zhao Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

This paper presents a three-step framework to remove the highlight exists on objects in certain conditions. Unlike traditional HDR (High Dynamic Range) technology requires multiple registrated image sequence; our method needs only two arbitrary images. SURF (Speeded Up Robust Features) matching algorithm is first applied to find corresponding point pairs between images; homography is then found by perspective transformation theory; minimum gray selection is used at last to eliminated the highlight and fuse related regions. Experimental results are given to demonstrate the performance of our method.

关键词： Feature extraction image color analysis Robustness Dynamic range Plastics Pixel Color

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Hierarchical interactive image segmentation using irregular pyramids

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2011年 6658 LNCS卷 245-254页

作者： Gerstmayer, Michael Haxhimusa, Yll Kropatsch, Walter G. Pattern Recognition and Image Processing Group Institute of Computer Graphics and Algorithms Vienna University of Technology Austria

ISBN: (纸本)9783642208430

In this paper we describe modifications of irregular image segmentation pyramids based on user-interaction. We first build a hierarchy of segmentations by the minimum spanning tree based method, then regions from different (granularity) levels are combined to a final (better) segmentation with user-specified operations guiding the segmentation process. Based on these operations the users can produce a final image segmentation that best suits their applications. This work can be used for applications where we need accuracy in image segmentation, in annotating images or creating ground truth among others. © 2011 Springer-Verlag Berlin Heidelberg.

关键词： image segmentation

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Unconstrained handwritten numeral recognition using Hausdorff distance and multi-layer neural network classifier

Unconstrained handwritten numeral recognition using Hausdorf...

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International Conference on Document Analysis and recognition

作者： Xuejing Wu Pengfei Shi Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)0769503187

A method for zip code recognition is presented. 2D binary images are input to HAVNET, a neural network which employs the Hausdorff distance as a similarity metric to train the weights which are required to represent the patterns learned by the network. A new learning rule for HAVNET is also introduced. In this approach, HAVNET is combined with a multilayer neural network. The Hausdorff distance acts as a zip code filter. Only the confusing digits are input into the multilayer network for training or recognition. Experimental results show that the correct-recognition rate with zero rejection is more than 97% for a database used by the Chinese mail sorting system.

关键词： Handwriting recognition Neural networks Multi-layer neural network pattern recognition Shape Optical character recognition software Euclidean distance image recognition Optical filters Postal services

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A PC algorithm for dynamic actuated traffic-control system

A PC algorithm for dynamic actuated traffic-control system

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International Conference on Intelligent Transportation

作者： Xingyu Zheng Zhonghua Liu Yuncai Liu InstituteImage Processing and Pattern Recognition University of Shanghai Jiaotong China Institute Image Processing and Pattern Recognition University of Shanghai Jiaotong China Department of the lost Imaging Processing and Pattern Recognition University of Shanghai Jiaotong China

ISBN: (纸本)0780381254

In this paper, we analyze the traditional algorithm (Circle->Phase) in the traffic-control system. And we propose a new algorithm that is proved better than the former one. By traffic flow simulation using advanced TSIS software, we get statistic data to analyze the characteristic of downstream traffic flow (DTF). Based on the mathematic model of DTF, we bring forward an algorithm to quickly decide the phase length and circle length. The algorithm adopts the real-time information according to required flow with the aim of minimizing the surplus time in each phase. It can adapt to any kind of traffic flow and has a high degree of flexibility.

关键词： Heuristic algorithms Traffic control Delay effects Algorithm design and analysis Analytical models Vehicle detection image recognition Road transportation Vehicle dynamics Statistical analysis

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Fault tolerant interval fusion for moving vehicle classification in wireless sensor networks

Fault tolerant interval fusion for moving vehicle classifica...

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IET International Communication Conference on Wireless Mobile and Computing (CCWMC 2009)

作者： C. T. Liu H. Huo T. Fang D. R. Li Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

Faults of sensor data will always present in sensor networks because of unreliable communication links, measurement interference and harsh environment. Developing fusion algorithms that can tolerate faults is necessary for reliable sensor network applications. In this paper, we study the fault tolerant fusion for moving vehicle classification based on Marzullo's interval fusion algorithm. The unreliable sensor data are represented using interval estimations. To reduce communication cost, quantized interval representation is adopted. Simulation results demonstrate the validity of the interval fusion algorithm. By using quantized representation, the communication cost is reduced.

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Facial Components Detection with Boosting and Geometric Constraints

Facial Components Detection with Boosting and Geometric Cons...

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International Conference on pattern recognition

作者： Tiesheng Wang Pengfei Shi Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)0769525210

An efficient framework utilizing both local features and geometrical distribution for detecting facial components is presented. First, candidate facial components are efficiently collected by cascaded boosting of Haar-like features. The candidates may include false positives and multiple detections. Then, geometrical distribution of facial components is imposed on the candidates to select the optimal configuration. For simplicity, we suppose full dependence between the components and model it with multivariate Gaussian. The effectiveness of the framework is evaluated with experiments

关键词： Face detection Boosting pattern recognition image processing Humans Eyes Mouth Nose Shape Face recognition

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