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Moshi Shibie yu Rengong Zhineng/pattern recognition and Artificial Intelligence 2009年第3期22卷 344-348页

作者： Sun, Bin Sang, Nong Li, Zheng Zheng, Qing-Qing State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute of Pattern Recognition and Artificial Intelligence Huazhong Univ. of Sci. and Technol. Wuhan 430074 China

The study of the second order motion in biological vision is a new source of inspiration for algorithms and research directions in computer vision. In this paper, the second order motion can be divided into three typical group according to the modulation types: spatial modulate motion, temporal modulate motion and spatio-temporal modulate motion. Experiments are conducted on the first order motion perception based on correlation model and the second order motion perception by correlation model preceded with a nonlinear process called texture grabber. The computational results are consistent with the previous suggestion that the second order motions are processed by nonlinear system.

关键词： Modulation

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Use Fukunaga-Koontz Transform to Solve Occlusion Problems in Multitarget Tracking

Use Fukunaga-Koontz Transform to Solve Occlusion Problems in...

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Chinese Conference on pattern recognition (CCPR)

作者： Yan Zhang Fanglin Wang Shengyang Yu Third Research Institute of Ministry of Public Security Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

For multitarget tracking problems, occlusions between targets are quite tough tasks. We present a novel algorithm to solve such problems. For the two targets in occlusions, Fukunaga-Koontz transform is exploited to achieve the projection matrix, with which the two targets are projected into a low dimensional space where they are quite distinguishing. To solve the problem of the change of target appearance, the eigenspace model is used as the probabilistic observation model, with which the algorithm can learn the changes of the target appearance online. These two procedures are evaluated in the particle filter based tracking framework. Experimental results demonstrated the effectiveness of our algorithm.

关键词： Target tracking Yttrium Particle filters Particle tracking Application software Equations Security image processing pattern recognition Computer vision

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Systematic methodology of multi-source information fusion for improving older drivers' safety

Systematic methodology of multi-source information fusion fo...

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IEEE Symposium on Intelligent Vehicle

作者： Li Xu Qunfei Zhao Chengbin Ma Fangfang Lu Institute of Image Processing and Pattern Recognition Shandong Jiaotong University Shanghai China UM-SJTU Joint Institute Shandong Jiaotong University Shanghai China

ISBN: (纸本)9781424435036

Drivers over the age of 65 are increasing rapidly in numbers and they are inclined to be involved in accidents frequently. In this paper, a multi-source information fusion model to improve the driving safety for older drivers is proposed. First, the influences of surrounding features, such as traffic and weather, on the driving safety are analyzed and the surrounding driving safety degree (SDSD) is proposed to represent it. Second, we analyze the effect of driving behavior characters on the driving safety and name it as the driving behavior safety degree (DBSD). Then we propose a fuzzy information fusion method to evaluate the driver safety degree (DSD) based on the evaluation results of SDSD and DBSD. The fuzzy reasoning rules can be adjusted to satisfy different drivers through analyzing the driving behavior and history traffic accident logs collected. We test our methods based on the data sets collected from the American National Highway Traffic Safety Administration (NHTSA) and the experimental results show that the proposed method is more efficient in improving the older driver's safety.

关键词： Vehicle safety Road accidents Vehicle crash testing Traffic control US Department of Transportation Road safety Automobiles Aging Alarm systems Intelligent vehicles

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A new tracking method for small infrared targets

A new tracking method for small infrared targets

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IEEE International Conference on image processing

作者： Lei Yang Weiping Lu Jie Yang Physics Department EPS Heriot-Watt University Edinburgh UK Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China

We report on a new approach to tracking small infrared targets. The method improves on existing target trackers by combining mean-shift tracker with Kalman filtering and by updating the tracking parameters through the measurement of the complexity of the target region. We have further developed a nonlinear algorithm to improve the robustness of the traditional mean-shift tracker for small infrared targets. Experimental results demonstrate a superior performance of our method compared to existing target trackers, particularly in the environment of strong measurement noise and large variation of illumination.

关键词： Target tracking Noise robustness Noise measurement Lighting Video sequences Kalman filters Filtering Particle measurements Working environment noise Robust stability

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A NEW LOCALIZED PHASE CONGRUENCY BASED OBJECT DETECTOR FOR X-RAY imageS

A NEW LOCALIZED PHASE CONGRUENCY BASED OBJECT DETECTOR FOR X...

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2009 International Conference on Machine Learning and Cybernetics(2009机器学习与控制论国际会议)

作者： XUE TIAN XU YANG Institute of Electrical and Mechanical Engineering Jiaxing University Jiaxing 314001 China Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai 200240

In this paper, we present a novel method for automatically computing phase congruency at appropriate scales and orientations. Compared with Kovcsi's phase congruency method, there are two distinct improvements in our method. First, our local phase information can be evaluated in a rotation invariant manner. Therefore, no orientation sampling is required. Second, the phase congruency is computed in a localized way, so there is no need to take all scales into consideration. Thus the computation load is reduced greatly and in the meanwhile this method can gain sub-pixel accuracy. We apply our algorithm to the endotracheal tube detection on X-ray image. Comparative experimental results show the efficiency of our method.

关键词： Phase congruency Feature eztraction Object detection image processing Scale space

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Predicting Soft Tissue Deformation Based on an Improved Biomechanical Model

Predicting Soft Tissue Deformation Based on an Improved Biom...

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International Conference on Information Technology and Computer Science, ITCS

作者： Shengzheng Wang Jie Yang Chaojian Shi Merchant Marine College Shanghai Maritime University Shanghai China Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

This paper presents an improved biomechanical model for the prediction of the soft tissues in the plastic surgical simulator. The new model is built on nonlinear finite mixed-element method (NFM-EM) in which the internal soft tissues (muscles and fat) are discretized into tetrahedral solid elements and the skin tissues into triangular shell elements, which distinguishes between the internal soft tissues and the skin in their geometrical structures, and addresses the non-homogenous problem of the facial soft tissues in their biomechanical characteristics. Moreover, after the investigation of the three different nonlinear strain-potential models, the biomechanical characteristics of the skin and the internal soft tissues are modeled with the most suitable one. The quantitative validation and the comparative results with other models illustrated the effectiveness of the approach on the simulation of complex cranio-facial surgery.

关键词： Biological tissues Deformable models Predictive models Skin Muscles Surgery Solid modeling Plastics Content addressable storage Biological materials

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A shadow detection method for remote sensing images using Affinity Propagation algorithm

A shadow detection method for remote sensing images using Af...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Huaiying Xia Xinyu Chen Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science and Technology Beijing Institute of Technology Beijing China

Shadow detection in high spatial resolution remote sensing image is very critical for locating geographical targets. In this paper, we proposed a new shadow detection method using Affinity Propagation (AP) algorithm in the Hue-Saturation-Intensity (HSI) color space. Because the pixel matrix is a large-scale matrix, if we apply AP algorithm directly on the raw pixel space, it will be computation intensive to calculate the similarity matrix. To solve this problem, we propose to divide the matrix into several blocks and then applying AP to detect shadows in H, S and I components respectively. Then, three detected images are fused to obtain a final shadow detection result. Comparative experiments are performed for K-means and threshold segmentation methods. The experimental results show that higher detection accuracy of the proposed approach is obtained, and it can solve the problems of false dismissals of K-means and threshold segmentation method.

关键词： Remote sensing image segmentation Space technology Shape Color Layout Histograms image processing Spatial resolution Object detection

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Investigating visual feature extraction methods for image annotation

Investigating visual feature extraction methods for image an...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Rukun Hu Shuai Shao Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China The School of Computer Science and Technology Beijing Institute of Technology Beijing China

In order to investigate the performance of visual feature extraction method for automatic image annotation, three visual feature extraction methods, namely discrete cosine transform, Gabor transform and discrete wavelet transform, are studied in this paper. These three methods are used to extract low-level visual feature vectors from images in a given database separately, then these feature vectors are mapped to high-level semantic words to annotate images with labels in a given semantic label set. As it is more efficient to depict the visual features of an image by the feature distribution than to resort to image segmentation technology for semantic image blocks, this paper is going to find out which of the three feature extraction methods performs better in image annotation based on the distribution of feature vectors from the image. The performance of three different kinds of feature extraction method is fully analyzed, and it is found that discrete cosine transform method is more suitable for Gaussian mixture model in automatic image annotation.

关键词： Feature extraction Discrete wavelet transforms Discrete cosine transforms Shape image databases Spatial databases Visual databases image analysis Performance analysis Bayesian methods

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Mobile Robot Position Identification with Specially Designed Landmarks

Mobile Robot Position Identification with Specially Designed...

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Japan-China Joint Workshop on Frontier of Computer Science and Technology (FCST)

作者： Huakang Li Long Zheng Jie Huang Chunlei Zhao Qunfei Zhao School of Computer Science and Engineering University of Aizu Aizu-Wakamatsu Japan Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

In this paper, we proposed a visual position calibration method using colored rectangle signboards for a mobile robot which is designed to work in a room environment. The rectangle signboards are placed in several known positions. Using Canny algorithm to detect the edge of color area to calculate the vanishing points in the image of the signboard, it is possible to obtain the relative direction and distance between the signboard and the robot by a single image. Experiments of position calibration were conducted. The results showed this method is effective and the errors between the set up positions and the experimental results were about 1.5 degrees and 3 cm in an array position.

关键词： Mobile robots image edge detection Robot vision systems Cameras Calibration Orbital robotics Navigation Relays Computer science Shape

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Invariant Primitives for Handwritten Arabic Script: A Contrastive Study of Four Feature Sets

Invariant Primitives for Handwritten Arabic Script: A Contra...

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International Conference on Document Analysis and recognition

作者： Sofiene Haboubi Samia Maddouri Noureddine Ellouze Hailkal El-Abed Image Processing and Pattern Recognition Unit National Engineering School of Tunis (ENIT) Tunis Tunisia Department of Signal Processing of Mobile Information Systems Institute for Communications Technology Brunswick Germany

ISBN: (纸本)9781424445004

The choice of relevant features is very decisive in handwriting recognition rate. Our aim is to present some useful structural and statistical features and see their degree of variability. In this paper, we start with a description of the variability of the Arabic handwriting and the way how to reduce it. Four kinds of feature sets used by our handwriting systems are then presented evaluated and discussed. The comparison is carried on a database of images from IFN/ENIT databases. The neural network multilayer perceptrons is our method of classification. A contrastive study of these primitives is done according to recognition their time and memory consuming and their variability degree.

关键词： Handwriting recognition image segmentation image analysis pattern recognition image recognition image databases Spatial databases Skeleton Data mining Text analysis

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