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ISPRS Workshop on Laser Scanning

作者： Lahamy, Herve Lichti, Derek Univ Calgary Dept Geomat Engn Calgary AB T2N 1N4 Canada

Several sensors have been tested for improving the interaction between humans and machines including traditional web cameras, special gloves, haptic devices, cameras providing stereo pairs of images and range cameras. meanwhile, several methods are described in the literature for tracking hand motion: the Kalman filter, the mean-shift algorithm and the condensation algorithm. In this research, the combination of a range camera and the simple version of the mean-shift algorithm has been evaluated for its capability for hand motion tracking. The evaluation was assessed in terms of position accuracy of the tracking trajectory in x, y and z directions in the camera space and the time difference between image acquisition and image display. Three parameters have been analyzed regarding their influence on the tracking process: the speed of the hand movement, the distance between the camera and the hand and finally the integration time of the camera. Prior to the evaluation, the required warm-up time of the camera has been measured. This study has demonstrated the suitability of the range camera used in combination with the mean-shift algorithm for real-time hand motion tracking but for very high speed hand movement in the traverse plane with respect to the camera, the tracking accuracy is low and requires improvement.

关键词： Hand motion tracking Range camera mean-shift algorithm Accuracy assessment

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Study of Missile Radiator Predicting and Tracking Technology on the basis of Kalman Filter and mean-shift algorithm

Study of Missile Radiator Predicting and Tracking Technology...

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International Conference on Manufacturing Science and Technology (ICMST 2011)

作者： Xu Zhen-hui Mao Bao-quan Xu Li Zhao Jun-yan Acad Armored Force Engn Dept Arms Engn Beijing Peoples R China

ISBN: (纸本)9783037852958

In order to improve the real-time character of missile radiator tracking and solve the predicting tracking problem when missile radiator shortly shelter or missing, it introduces moving target predicting and tracking technology. According to the predicting and tracking method, it proposes three predicting and tracking overall schemes of missile radiator based on Kalman filtering and improved mean-shift algorithm. Also it compares the real-time character of three kinds of schemes. According to the trajectory character of missile radiator, it constructs Kalman filter. The experiment results indicate that by using Kalman filtering technology, there are improvements in real-time character and shortly shelter or missing problem can be solved well. It plays a certain compensation function to the whole system.

关键词： missile radiator mean-shift algorithm Kalman filtering predicting and tracking technology

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Human Body Tracking System Based on DWT and mean-shift algorithm on ARM-Linux Platform

Human Body Tracking System Based on DWT and Mean-Shift Algor...

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World Congress on Information and Communication Technologies (WICT)

作者： Rakate, Ganesh Vishwakarma Inst Technol Dept Instrumentat Engn Pune Maharashtra India

ISBN: (纸本)9781467348041

A modified human body tracking system based on Discrete Wavelet Transform (DWT) and mean-shift algorithm is proposed. Most of the traditional object tracking systems have many disadvantages like complexity, high computation power and large size. Here, whole system is implemented on ARM-Linux platform with camera mounted on rotary platform. DWT divides a frame into four different frequency bands without losing spatial information. So it neglects most of the fake motions in background as they are decomposed into high frequency wavelet sub-band. Color and spatial information are used as tracking parameters. mean-shift algorithm takes less number of calculations while converging to new object search window. Ultimate aim of this project is to implement single human body tracking system on ARM-Linux platform, for which minimum computations should be performed. Combination of DWT and mean-shift algorithm significantly decreases computation power. As shown in results, human body tracking system is successfully implemented.

关键词： Human Body Tracking Discrete Wavelet Transform Spatial Information mean-shift algorithm ARM OpenCV Linux

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Human Tracking Method Based on Multi-Template Color-Texture mean-shift algorithm 12

Human Tracking Method Based on Multi-Template Color-Texture ...

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IEEE International Conference on Mechatronics & Automation

作者： Wen, Linfeng Jia, Songmin Wang, Lijia Beijing Univ Technol Coll Elect & Control Engn Beijing 100124 Peoples R China Beijing Key Lab Computat Intelligence & Intellige Beijing 100124 Peoples R China Minist Educ Engn Res Ctr Digital Community Beijing 100124 Peoples R China

ISBN: (纸本)9781479970988

Human tracking is a hot topic and a challenging task during the past few decades. This paper present a multi templates based strategy for human detecting and tracking with a mobile robot. This method first determines the coarse location by using adaptive template matching algorithm (ATM) based on head-shoulder. Then, a multi-templates based method is presented to locate the person precisely. Multi templates considering the pose changes are obtained to represent the person. For each template, the mean-shift is proceeded. Then, the accurate position is obtained by fusing the results of the mean-shift from all the templates. After detecting the person, the templates are updated by considering the likelihood of the tracking results and the old templates. Finally, the method is evaluated on a mobile robot in complex environment. The experiment result shows that our method performs well when there are unclear disparity image and pose variations.

关键词： Human tracking Head-shoulder matching mean-shift algorithm Multi-template

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OBJECT TRACKING BY APPLYING mean-shift algorithm INTO PARTICLE FILTERING

OBJECT TRACKING BY APPLYING MEAN-SHIFT ALGORITHM INTO PARTIC...

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2nd IEEE International Conference on Broadband Network and Multimedia Technology

作者： Wang Hongling Yang Bo Tian Guodong Men Aidong Beijing Univ Posts & Telecommun Lab Broadband Multimedia Commun Beijing 100088 Peoples R China

ISBN: (纸本)9781424450053

In the pursuit of robust object tracking, both particle filter and mean-shift algorithm have proven successful approaches. Also both of them have weaknesses. The article presents the integration of mean-shift algorithm with particle filtering during the moving object tracking. In our method mean-shift algorithm is used in the sampling steps of particle filtering, which efficiently reduces the number of sampled particles. That integrates the advantages of mean-shift algorithm and particle filtering. When applied in the moving object tracking, our method proved to be more robust and time saving compared with the conventional particle filtering and mean shift algorithm.

关键词： object tracking particle filtering mean-shift algorithm

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Moving Target Tracking Based on LogGabor Wavelet and mean-shift algorithm

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Semiconductor Photonics and Technology 2009年第2期15卷 81-85,96页

作者： DU Xian-yan HAN Xiao-jun LU Wei-wei Department of Information and Communication Tianjin Polytechnic University Tianjin 300160 CHN

Tracking moving target from image or video sequence is a hot research topic in computer vision. An algorithm based on LogGabor wavelet and mean-shift has been proposed for moving target tracking under fixed camera setting and complicated environment. Phase coherency of LogGabor wavelet facilitates to extract the edge of moving target and check noise. According to the edge detection,the starting location of mean-shift can be estimated using the target center coordinate. Eventually,a real-time moving target can be extracted by doing iterative matching pursuit,and experimental results proved the effectiveness of the method proposed.

关键词： mean-shift algorithm phase congruency LogGabor wavelet transformation target tracking

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Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based mean-shift algorithm

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SENSORS 2017年第7期17卷 1693-1693页

作者： Yang, Mengzhao Song, Wei Mei, Haibin Shanghai Ocean Univ Coll Informat Technol Shanghai 201306 Peoples R China

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient.

关键词： remote sensing (RS) fast retrieval ocean disasters mean-shift algorithm Hadoop system pyramid HDFS storage

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Dynamics of a mean-shift-like algorithm and its applications on clustering

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INFORMATION PROCESSING LETTERS 2013年第1-2期113卷 8-16页

作者： Liu, Yiguang Li, Stan Z. Wu, Wei Huang, Ronggang Sichuan Univ Vis & Image Proc Lab Sch Comp Chengdu 610064 Sichuan Provinc Peoples R China Chinese Acad Sci CBSR Inst Automat Beijing 100080 Peoples R China Chinese Acad Sci NLPR Inst Automat Beijing 100080 Peoples R China Sichuan Univ Sch Elect & Informat Engn Chengdu 610064 Sichuan Provinc Peoples R China

The mean-shift (MS) algorithm and its variants have wide applications in pattern recognition and computer vision tasks such as clustering, segmentation, and tracking. In this paper, we study the dynamics of the algorithm with Gaussian kernels, based on a Generalized MS (GMS) model that includes the standard MS as a special case. First, we prove that the GMS has solutions in the convex hull of the given data points. By the principle of contraction mapping, a sufficient condition, dependent on a parameter introduced into Gaussian kernels, is provided to guarantee the uniqueness of the solution. It is shown that the solution is also globally stable and exponentially convergent under the condition. When the condition does not hold, the GMS algorithm can possibly have multiple equilibriums, which can be used for clustering as each equilibrium has its own attractive basin. Based on this, the condition can be used to estimate an appropriate parameter which ensures the GMS algorithm to have its equilibriums suitable for clustering. Examples are given to illustrate the correctness of the condition. It is also shown that the use of the multiple-equilibrium property for clustering, on the data sets such as IRIS, leads to a lower error rate than the standard MS approach, and the K-means and Fuzzy C-means algorithms. (c) 2012 Elsevier B.V. All rights reserved.

关键词： Design of algorithms mean-shift algorithm Stability Exponential convergence Clustering

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Gaussian mean-shift is an EM algorithm

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2007年第5期29卷 767-776页

作者： Carreira-Perpinan, Miguel A. Oregon Hlth & Sci Univ Dept Comp Sci & Elect Engn OGI Sch Sci & Engn Beaverton OR 97006 USA

The mean-shift algorithm, based on ideas proposed by Fukunaga and Hostetler [ 16], is a hill-climbing algorithm on the density defined by a finite mixture or a kernel density estimate. mean-shift can be used as a nonparametric clustering method and has attracted recent attention in computer vision applications such as image segmentation or tracking. We show that, when the kernel is Gaussian, mean-shift is an expectation-maximization ( EM) algorithm and, when the kernel is non-Gaussian, mean-shift is a generalized EM algorithm. This implies that mean-shift converges from almost any starting point and that, in general, its convergence is of linear order. For Gaussian mean-shift, we show: 1) the rate of linear convergence approaches 0 ( superlinear convergence) for very narrow or very wide kernels, but is often close to 1 ( thus, extremely slow) for intermediate widths and exactly 1 ( sublinear convergence) for widths at which modes merge, 2) the iterates approach the mode along the local principal component of the data points from the inside of the convex hull of the data points, and 3) the convergence domains are nonconvex and can be disconnected and show fractal behavior. We suggest ways of accelerating mean-shift based on the EM interpretation.

关键词： mean-shift algorithm Gaussian mixtures kernel density estimators EM algorithm clustering

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mean-shift Tracking algorithm based on Kalman Filter using Adaptive Window and Sub-blocking 11

Mean-Shift Tracking Algorithm based on Kalman Filter using A...

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11th World Congress on Intelligent Control and Automation

作者： Wang, Xingmei Hu, Zhihao Feng, Jingjiao Li, Lin Harbin Engn Univ Comp Sci & Technol Harbin Heilongjiang Pr Peoples R China Harbin Engn Univ Informat & Commun Engn Harbin Heilongjiang Pr Peoples R China

ISBN: (纸本)9781479958252

To reduce the tracking errors caused by highspeed motion and variable motion in the process of moving target tracking, a novel mean-shift tracking algorithm based on Kalman filter using adaptive window and sub-blocking is proposed in this paper. Moving target's utmost position is predicted by combining Kalman filter and historical information, which is used as the initial position. During describing feature model of target and candidate regions, they are blocked and each sub-block region is processed by reducing RGB interval, by which computational efficiency will be improved. Finally, window bandwidth will be enlarged and reduced according to Bhattacharyya coefficient, and it achieves accurate moving target tracking by adaptive window. The comparison experiments of the Coastguard standard image sequence and car image sequence demonstrate that the proposed tracking algorithm is insensitive to high-speed motion and variable motion of moving target, and it has better tracking performance.

关键词： Moving target tracking mean-shift algorithm Kalman filter algorithm Sub-blocking

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