基于混沌动力学模型的群体目标检测与分类

山东大学学报(工学版) ›› 2010, Vol. 40 ›› Issue (2): 19-23.

基于混沌动力学模型的群体目标检测与分类

乔伟¹,王汇源^1,2,吴晓娟¹,刘鹏威¹

1. 山东大学信息科学与工程学院, 山东济南 250100;
2. 阿维罗大学电子与电信研究所, 葡萄牙阿维罗 3810-193

收稿日期:2009-03-18 出版日期:2010-04-16 发布日期:2009-03-18
作者简介:乔伟（1984-），男，山东德州人，硕士研究生，主要研究方向为图像处理、视觉跟踪. E-mail: dlanglang@yahoo.cn
基金资助:
国家自然科学基金资助项目（60675024）

Crowd object detection and classification based on a chaotic dynamic model

QIAO Wei¹, WANG Hui-yuan^1,2, WU Xiao-juan¹, LIU Peng-wei¹

1. School of Information Science and Engineering, Shandong University, Jinan 250100, China;
2. IEETA, Universidade de Aveiro, Aveiro, 3810-193, Portugal

Received:2009-03-18 Online:2010-04-16 Published:2009-03-18

摘要/Abstract

摘要：

传统目标跟踪检测方法对多目标情况处理已较为困难,对群体目标监测和跟踪更是难以解决的问题。因此考虑在拉格朗日混沌动力学基础上实现对视频群体流的分割以及相关检测。把群体运动系统作为混沌动力学系统处理,而群体目标则作为流动的粒子群处理,粒子的流动以流图(flow map, FM)进行跟踪。在此基础上可以获得有限时间李亚普诺夫指数(finite time Lyapunov exponent, FTLE)场,形态学处理后,对群体流动区域进行提取并对结果分类。实验结果验证了该方法的有效性。

关键词: 群体目标检测, 有限时间李亚普诺夫指数, 轮廓提取

Abstract:

Multi-object detection and tracking is an arduous task for traditional methods, and objects in crowds are more difficult to deal with. In this paper,segmentation and detection to video crowd flow was realized by a chaotic dynamics based method. The crowd moving system was treated as a chaotic dynamic system, and object in crowds were treated as particles, whose flow is tracked by flow map. As a result, the finite time Lyapunov exponent (FTLE) field was obtained. After morphological processing, region extraction and classification can be achieved. Experimental results indicate the effectiveness of the proposed approach.

Key words: crowd object detection, finite time Lyapunov exponent, contour extraction

乔伟1,王汇源1,2,吴晓娟1,刘鹏威1. 基于混沌动力学模型的群体目标检测与分类[J]. 山东大学学报(工学版), 2010, 40(2): 19-23.

QIAO Wei1, WANG Hui-yuan1,2, WU Xiao-juan1, LIU Peng-wei1. Crowd object detection and classification based on a chaotic dynamic model[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2010, 40(2): 19-23.

参考文献

多维度评价

Viewed

Full text

Abstract

Cited

Shared

Discussed

[1]	左俊彦, 张建国, 钟涛. 基于Canny检测的股骨边缘轮廓连接算法[J]. 山东大学学报(工学版), 2015, 45(3): 65-72.
[2]	丛奎荣韩杰常发亮. 视觉机器人货物轮廓提取与定位[J]. 山东大学学报(工学版), 2010, 40(1): 15-18.
[3]	方挺,杨忠,沈春林 . 无人机编队视频序列中的多目标精确跟踪[J]. 山东大学学报(工学版), 2008, 38(4): 22-26 .