English  |  正體中文  |  简体中文  |  Items with full text/Total items : 26988/38789
Visitors : 2351687      Online Users : 29
RC Version 4.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Adv. Search
LoginUploadHelpAboutAdminister

Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44197

Title: Suspicious Object Detection for Robbery Event Analysis Using Ratio Histogram
Authors: Chi-Hung Chuang,
Jun-Wei Hsieh
Kao-Chin Fan
Contributors: 國立臺灣海洋大學:資訊工程學系
NTOU:Department of Computer Science and Engineering
Keywords: Object detection
Event detection
Humans
Videos
Biological system modeling
Hidden Markov models
Packaging
Trajectory
Color
Shape
Date: 2007-08
Issue Date: 2017-11-16
Publisher: 2007 First International Workshop on Multimedia Analysis and Processing
Abstract: Abstract:This paper proposes a novel method to detect suspicious objects from videos for robbery event analysis. First of all, a background subtraction using a minimum filter is used for detecting foreground objects from videos. Then, a novel kernel-based tracking method is proposed for tracking each moving object and obtaining its trajectory. Then, we propose a novel robbery event analysis system to analyze suspicious object transferring conditions between any two persons. Usually, when a robbery event happens, there should some suspicious object transferring conditions happening between the robbery and the victim. Since there is no prior knowledge about the object's property, it is difficult to automatically analyze the conditions without any manual efforts. To tackle this problem, a novel ratio histogram is then proposed for finding suspicious objects and then accurately analyzing their transferring conditions. After color re-projection, we use Gaussian mixture models to model the suspicious object's visual properties so that it can be very accurately segmented from videos. After analyzing its subsequent speed, different robbery events can be then effectively detected from videos. Experiment results have proved that the proposed method is robust, accurate, and powerful in robbery event detection.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44197
Appears in Collections:[資訊工程學系] 演講及研討會

Files in This Item:

File Description SizeFormat
index.html0KbHTML41View/Open


All items in NTOUR are protected by copyright, with all rights reserved.

 


著作權政策宣告: 本網站之內容為國立臺灣海洋大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,請合理使用本網站之內容,以尊重著作權人之權益。
網站維護: 海大圖資處 圖書系統組
DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback