A method for detecting pedestrians in video surveillance scenes
- Resource Type
- Conference
- Authors
- Zhang, Xin; Gao, Yuehua; Wang, Xiaotao; Li, Jianing; Wang, Bing
- Source
- 2012 International Conference on Systems and Informatics (ICSAI2012) Systems and Informatics (ICSAI), 2012 International Conference on. :2016-2019 May, 2012
- Subject
- Power, Energy and Industry Applications
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Humans
Lighting
Skin
Head
Image color analysis
Feature extraction
Mathematical model
Pedestrian detection
human skin color
adaptive ambient lighting
Hough transform
circle contour detection
- Language
Detecting pedestrian accurately from natural scenes makes the important impact on intelligent video surveillance. In this paper, we combine motion information, human skin color information, human shape information and variation of ambient lighting to detect pedestrians for the application of automated video surveillance. The moving objects in the video sequence images are extracted using the multi-frame differencing method with adaptive ambient illumination changes. The adaptive ambient illumination human skin feature extraction algorithm extracts human skin color in different lighting changes in order to tackle the problem that skin color is susceptible to illumination. Improve Hough transform is used to automatically determine the size of human head in different scenes. The experimental results show that the method presented in this paper is feasible and is suitable for online applications in moving human detection in natural scenes.