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一种基于快速 MEANSHIFT 的目标跟踪系统。

A fast MEANSHIFT algorithm-based target tracking system.

机构信息

State Key Laboratory for Strength & Vibration, School of Aerospace, Xi'an Jiaotong University, Xi'an 710049, China.

出版信息

Sensors (Basel). 2012;12(6):8218-35. doi: 10.3390/s120608218. Epub 2012 Jun 13.

DOI:10.3390/s120608218
PMID:22969397
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3436026/
Abstract

Tracking moving targets in complex scenes using an active video camera is a challenging task. Tracking accuracy and efficiency are two key yet generally incompatible aspects of a Target Tracking System (TTS). A compromise scheme will be studied in this paper. A fast mean-shift-based Target Tracking scheme is designed and realized, which is robust to partial occlusion and changes in object appearance. The physical simulation shows that the image signal processing speed is >50 frame/s.

摘要

使用主动摄像机跟踪复杂场景中的运动目标是一项具有挑战性的任务。跟踪精度和效率是目标跟踪系统(TTS)的两个关键但通常不兼容的方面。本文将研究一种折衷方案。设计并实现了一种快速基于均值漂移的目标跟踪方案,该方案对部分遮挡和目标外观变化具有鲁棒性。物理模拟表明,图像处理速度>50 帧/秒。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/5b9c5df434b0/sensors-12-08218f13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/96552ed42e2b/sensors-12-08218f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/a155363ab065/sensors-12-08218f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/3900c8cb873c/sensors-12-08218f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/0e727b2e3937/sensors-12-08218f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/db99482e1f45/sensors-12-08218f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/5232337974ed/sensors-12-08218f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/143b10f9a326/sensors-12-08218f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/3cc148a077ae/sensors-12-08218f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/6d699bfdc873/sensors-12-08218f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/cdf72d098d7c/sensors-12-08218f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/a65d1759b3b7/sensors-12-08218f11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/7795a7b87476/sensors-12-08218f12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/5b9c5df434b0/sensors-12-08218f13.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/96552ed42e2b/sensors-12-08218f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/a155363ab065/sensors-12-08218f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/3900c8cb873c/sensors-12-08218f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/0e727b2e3937/sensors-12-08218f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/db99482e1f45/sensors-12-08218f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/5232337974ed/sensors-12-08218f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/143b10f9a326/sensors-12-08218f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/3cc148a077ae/sensors-12-08218f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/6d699bfdc873/sensors-12-08218f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/cdf72d098d7c/sensors-12-08218f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/a65d1759b3b7/sensors-12-08218f11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/7795a7b87476/sensors-12-08218f12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9cc3/3436026/5b9c5df434b0/sensors-12-08218f13.jpg

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3
Fast template matching with polynomials.基于多项式的快速模板匹配
IEEE Trans Image Process. 2007 Aug;16(8):2139-49. doi: 10.1109/tip.2007.901243.
4
Optimal approach for fast object-template matching.快速目标模板匹配的优化方法。
IEEE Trans Image Process. 2007 Aug;16(8):2048-57. doi: 10.1109/tip.2007.901819.
5
An active vision system for multitarget surveillance in dynamic environments.一种用于动态环境中多目标监视的主动视觉系统。
IEEE Trans Syst Man Cybern B Cybern. 2007 Feb;37(1):190-8. doi: 10.1109/tsmcb.2006.883423.
6
Online selection of discriminative tracking features.区分性跟踪特征的在线选择。
IEEE Trans Pattern Anal Mach Intell. 2005 Oct;27(10):1631-43. doi: 10.1109/TPAMI.2005.205.
7
Asymptotic convergence rate of the EM algorithm for gaussian mixtures.高斯混合模型的期望最大化(EM)算法的渐近收敛速率
Neural Comput. 2000 Dec;12(12):2881-907. doi: 10.1162/089976600300014764.