Conference Program of WCICA 2012

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Conference Program WCICA 2012 through the video frames. After that the step is the selection of the 20 optimal key facial points, those which change the most with changes in expression. Since the distance of geometric features, a set of displacement vectors, is of a high dimensions, it is mapped into a low dimensional space, called feature space, by applying PCA expansion. Then estimation of input image is achieved by projecting it on to the feature space. After build the feature space, we trained SVM classification and tested it for result. ◁ PSaC-47 Sequence Detection of Planetary Surface Craters From DEM Data, pp.4775–4779 Yu, Zhengshi Zhu, Shengying CUI, Pingyuan Beijing Inst. of Tech. Beijing Inst. of Tech. Beijing Inst. of Tech. The research on identification and recognition of impact craters on planetary surface is focused on how to detect them from background. A novel sequence algorithm is proposed to crater detection that utilizes DEM data instead of images. By investigating the features of ideal craters, several constraints can be developed to extract candidate crater edges from other topographies. Based on the fact that the shape of most craters is approximate to an ellipse, the Least Median Square Ellipse Fitting Method can be used to exclude pseudo-edges, and to reserve the real edges which contain the feature of the crater. The location, orientation and other physical parameters of the crater can be determined by fitting real edges to an ellipse based on Robust Least Square Method. Mathematical simulations are performed with the moon DEM data. The results show that the topography-based crater detection algorithm offers an effective method for identification and characterization of ellipse-like impact craters, and the accuracy is high enough. ◁ PSaC-48 A video tracking method based on Niche Particle Swarm Algorithm- Particle Filter, pp.4780–4783 Li, Xin Chen, Wenjie Shang, Zengguang Beijing Inst. of Tech. Beijing Inst. of Tech. The Chinese people’s liberation army In order to improve the stability and robustness in video tracking based on particle filter. We proposed Niche Particle Swarm Algorithm-Particle Filter (NPSA-PF) which applies Niche Particle Swarm Algorithm to the re-sampling stage in particle filter. The ability of Niche Particle Swarm Algorithm which improves the particles’local search ability and weakens the information sharing between particles, effectively reduces the tracking particles number and improves tracking stability and robustness. We use it in video tracking and the performance is validated to be effective. ◁ PSaC-49 An Efficient Approach of 3D Ear Recognition, pp.4784–4790 Wang, Kai Mu, Zhichun He, Zhijun Univ. of Sci. & Tech. Beijing School of Automation & Electrical Engineering, Univ. of Sci. & Tech. Beijing China Nuclear Power Engineering Co.,Ltd The Iterative Closest Point(ICP) algorithm is usually used for 3D ear recognition in the literatures. However, the high computational cost of ICP limits the application of 3D ear biometrics. In this paper, we present an efficient approach based on local feature and ICP for 3D ear recognition. The local features are detected and represented with LSP(Local Surface Patch), and used to compute the initial transformation for matching with ICP. An elite preservation strategy is introduced to refine the candidate gallery ears that a modified ICP algorithm with kd-tree index, distance and uniqueness constraints is applied to. The proposed approach achieved a rank-1 recognition rate 98.55% on Collection J2 of UND biometrics datasets. Matching an ear with a gallery requires only 1.73 sec on average. ◁ PSaC-50 A new method on Solving Correlation Dimension of Chaotic Timeseries, pp.4820–4824 Qiao, Meiying Ma, Xiaoping China Univ. Mining & Tech. China Univ. of Mining & Tech. Traditional G-P algorithm exist two drawbacks in solving the correlation dimension of chaotic time series. The one is the subjective existence to determine scaleless range, the other is calculation error is large when the amount of data is small. For two shortcomings, the fuzzy C-means clustering is introduced to the G-P algorithm to determine the no-scales range. Least-squares fitting method is used to find the saturation correlation dimension value in determining the scalelesss range. Using different amount of Loren and Rossler data, such as 500,1000,2000,5000 and 10000, verify the improved algorithm in this paper,. Simulation results show that the error relatively small if the delay time is small when the amount of 500, 1000 and 2000. With the length of data increases, the cluster centre value of the slope relatively flat closer to their ideal value. The conclusions are applicable to Lorenz and Rossler data. ◁ PSaC-51 3D Ear Modeling Based on SFS, pp.4837–4841 Liu, Cong Mu, Zhichun Wang, Kai Zeng, Hui Univ. of Sci. & Tech. Beijing School of Automation & Electrical Engineering, Univ. of Sci. & Tech. Beijing Univ. of Sci. & Tech. Beijing Univ. of Sci. & Tech. beijing Ear recognition, by using ear for identification recognition, is a kind of new biometric identification technology. Currently there are a lot of ear recognition methods based on 2D images, while 3D data can provide more information. 3D reconstruction methods based on multiple 2D images have a common difficult which is to extract corresponding feature points of different images. In this paper, SFS(Shape From Shading) was used for 3D modeling by only one grayscale image. Light direction was estimated by analyzing singular points, which refers to the greatest grayscale point, in 2D grayscale image. In addition, in order to achieve more accurate 3D modes, the abnormal high brightness of the cavity of auricular concha is processed. The matching accuracy of the model can reach to 84%. Therefore the experiments shown that the method proposed in this paper is simple and effective to modeling 3D ear. ◁ PSaC-52 A Target Detection Method in Dynamic Scene Based on Harris Algorithm with Sub-block Threshold, pp.4842–4847 Lu, Jinghua LEI, Yinghui Chen, Jie Zhang, Juan Beijing Inst. of Tech. Beijing Inst. of Tech. Beijing Inst. of Tech. Beijing Inst. of Tech. In this paper, an improved Harris algorithm for the target detection in dynamic scene due to the camera motion is presented. First, a sub-block thresholding method is proposed to solve the problem of uneven distribution of corners detected by Harris algorithm. Then, the improved Harris algorithm is used to extract feature points, which are used to estimate the parameters of global motion with the random-max consistency algorithm and the least-square method. Compensated by the result parameters, the reference image together with the current image are used to detect the target with the frame difference method. Experiment results show that the algorithm can detect the moving target more accurately in dynamic scene. ◁ PSaC-53 Robust Visual Tracking with Classifier-like Appearance Model and Entropy Particle Filter, pp.4853–4858 Song, Yu Li, Qingling Yan, Deli Kang, Yifei Beijing Jiaotong Univ. China Univ. of Mining & Tech., Beijing Beijing Jiaotong Univ. beijing jiaotong Univ. The detection based visual tracker treats tracking as the object and its surround background online classification problem. There are two main difficult issues in this method: one is to specify exact labels for the online samples, the other is to avoid template drift that caused by wrong update of the classifier-like appearance model. To overcome 198
WCICA 2012 Book of Abstracts: Saturday Sessions the problems, a novel tracking algorithm based on online Multiple Instance Learning (MIL) and entropy particle filter is proposed. Main contributions of our work are: (1) we introduce MIL in particle filter visual tracking framework to reduce the online training error of the classifierlike appearance model; (2) the appearance model consists of an initial fixed MIL classifier and an online dynamic MIL classifier; (3) a particle set maximum negative entropy criterion is designed to online fuse the two classifiers. Experimental results verify the effectiveness of the proposed algorithm. ◁ PSaC-54 Abnormal Detection based on Gait Analysis, pp.4859–4864 Wang, Chao Wu, Xinyu Li, NanNan Chen, Yen-Lun Inst. of Advanced Integration Tech. Shenzhen Inst.s of Advacned Tech., CAS shenzhen Inst. of advanced Tech. of chinese Acad. of Sci. Shenzhen Inst. of Advanced Tech., Chinese Acad. of Sci. Abnormal behavior detection has recently gained growing interest from computer vision researchers. In this paper, the gait-analysis-based abnormal detection is proposed for walking scenes, where gaits of people are analyzed in all kinds of situations and the gait data are utilized to construct the basic gait model. Walking people in the crowd are tracked and their activities silhouettes are abstracted and compared with the basic gait model. Some of those activities which are significantly difference with the basic gait models are defined as abnormal behavior, where the activities silhouettes and gait models are measured by chamfer distance. The experiments verify that our system could effectively detect several kinds of activities different with walking. ◁ PSaC-55 An Improved Kernelized Discriminative Canonical Correlation Analysis and Its Application to Gait Recognition, pp.4869–4874 WANG, KEJUN YAN, TAO Harbin Engineering Univ. Harbin Engineering Univ. Based on the canonical correlation analysis (CCA) and its extended algorithms, an improved kernelized discriminative canonical correlation analysis (KDCCA) was proposed in this paper. Compared with the existing KDCCA, there were two improvements. Firstly, when the kernel method was added,by improving the optimization objective function, the correlation between the final canonical correlation characteristics of the non-corresponding elements were reduced and improved classification results. Secondly, a more general class relationship matrix without sorting the samples was used for adding the class information. Finally, the proposed method was applied to gait recognition to solve the multi-view and different states problem. Experimental results show that the proposed method performs satisfactory recognition results. ◁ PSaC-56 Head Detection Based on 21HT and Circle Existence Model, pp.4875– 4880 Zhao, Min Sun, Dihua Tang, Yi He, Hengpan Chongqing Univ. Chongqing Univ. Chongqing Univ. ChongQing Univ. A novel method for head detection was proposed in video sequences captured with fixed vertical mono-camera, which integrated hough transformation, hair-color distribution model and circle existence model. Target area was firstly detected using fast gradient hough transformation (FGHT). In order to overcome head area mis-detection and incapability of locating head area introduced by FGHT, hair-color classification was used to filter the candidate targets through modeling hair-color distribution. Furthermore, based on non-parameter probability theory, the probability of circle existence model was established, which finalized the stages of head detection by locating the head. Compared with average circle detection algorithm, experimental results indicate that the proposed head detection algorithm can eliminate false targets and greatly increase accuracy. ◁ PSaC-57 A Three Dimension Reconstruction method on a kind of Micro and Thin Laser Seam, pp.4881–4886 Wang, Liwei Chen, Haiyong Sun, Hexu Xing, Guansheng Hebei Univ. of Tech. Hebei Univ. of Tech. Hebei Univ. of Tech. Hebei Univ. of Tech. The laser weld is becoming more and more popular in the steel industrial production. However, the varying illumination, reflection and splatter lead to the irregular seam shape, which deteriorates the seam quality. In order to evaluate the seam shape and its quality, a 3D reconstruction method about micro and thin laser seam is proposed. The line structured light stripe is projected on the laser seam to be measured by a projector, and deformation of the stripe is captured by a CCD camera with industrial microscope lens. An image processing method that can efficiently locate the deformation of the stripe in the image plane is p- resented. Also, a novel procedure to automatically define the region of interest in the image is proposed. And then a straight line and curve fit is used to reduce the harm of the various disturbances and accurately gain the centre line of stripe. Furthermore, the characteristic points of the seam are obtained by using the distance search method. Finally, the proposed reconstruction method is applied to laser seam specimen, the desired performances are gained, and the results are satisfying. ◁ PSaC-58 A Novel 3D Ear Reconstruction Method Using a Single Image, pp.4891–4896 Li, Chen Mu, Zhichun Zhang, Feng Wang, Shuai Univ. of Sci. & Tech. Beijing School of Automation & Electrical Engineering, Univ. of Sci. & Tech. Beijing The First Research Inst. of Ministry of Public Security of P.R.C Univ. of Sci. & Tech. Beijing To achieve denser 3D ear model from less controlled 2D image, we explore a 3D Ear Morphable Model (3DEMM) for 3D ear reconstruction using a single 2D ear image. Considering the unique structure of ear, we propose a Triangle Mesh Hierarchical Growth (TMHG) based dense corresponding method. The proposed method can overcome the shortcoming of optical flow based method and achieve pixel level dense correspondences based on physiological features of ear without choosing a reference ear. Novel 3D ear shape can be recovered from a single ear image based on the proposed 3D ear morphable model. Extensive experimental results have shown that our proposed method can obtain denser 3D ear model with lower cost and higher efficiency than existing methods. ◁ PSaC-59 Spherical Terrain Matching for SLAM in Planet Exploration, pp.4907– 4911 Pan, Haining CUI, Pingyuan Wang, Huan Beijing Univ. of Tech. Beijing Inst. of Tech. Beijing Inst. of Tech. This paper describes a scan matching algorithm for motion estimation near a planet surface using scanning laser scanner data in spherical coordinate. It is directly based on range finding data and followed by point to point terrain map alignment in the laser scanner’s spherical coordinate system. Laser scan matching of current and reference s- cans are enhanced by weighted terrain and distortion compensation. It is also accelerated by predicted vision window using inner dynamic model and SLAM results. The algorithm is tested using data acquired within virtual OpenGL environment and proved to be efficient for scan matching with terrain distortion. ◁ PSaC-60 Good Resolutions for Hough Transform, pp.4916–4920 Tu, Chunling Van Wyk, Barend Tshwane Univ. of Tech. Tshwane Univ. of Tech. 199
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WCICA 2012 The 10 th World Congress
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