Multiple People Visual Tracking in a Multi-Camera System for Cluttered Environment
Date Issued
2005
Date
2005
Author(s)
Cheng, Yu-Shan
DOI
zh-TW
Abstract
This thesis aims to track multiple people in a multi-camera system for cluttered environment which can be divided into two important parts: one is tracking multiple people in a single camera environment, and the other is tracking multiple people in a multi-camera environment.
In a single camera environment, we apply the motion detector and the ellipse algorithm to detect a new person intruding the surveillance area. Then, we utilize the template matching and the ellipse matching to track the person. To prevent tracking failure tracking when people cross over each other, we include the hereby proposed Joint Visual Probabilistic Data Association filter (JVPDA filter) to track multiple people successfully.
In a multi-camera environment, the major problem is to determine whether the new person intruding into some surveillance area of a camera is an identified person by some other camera or not. To resolve the aforementioned problem, we propose an approach called consistence labeling. After such labeling process, we track this person by the JVPDA algorithm. Finally, effectiveness of this tracking algorithm is validated via extensive experiments.
Subjects
運動偵測
橢圓演算法
模版比對
聯合機率資料連結
多人物追蹤
多相機系統
身份辨識
Motion Detector
Ellipse Algorithm
Template Matching
Joint Visual Probabilistic Data Association
Multiple People Tracking
Multi-camera System
Consistence labeling
Type
thesis
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