Moving object detection in video sequences

DOI

10.2991/ammee-17.2017.77How to use a DOI?

Keywords

Moving object detection, Adaptive Gauss mixture background model, local texture features, YCbCr color features, Shadow detection.

Abstract

Moving object detection belongs to the primary processing stage of visual analysis, as well as the premise and basis of object tracking and behavior analysis. Foreground motion images containing shadows are obtained by an adaptive Gauss mixture background model. To better remove shadows and get moving objects, this paper has proposed a shadow detection algorithm based on local texture feature and YCbCr color features to detect shadow images, then, shadow images are subtracted from foreground motion images, and the final moving object is obtained by filtering and contour filling, which better achieves the detection of moving objects in video sequences.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Di Ren
AU  - Bing Xu
PY  - 2017/06
DA  - 2017/06
TI  - Moving object detection in video sequences
BT  - Proceedings of the Advances in Materials, Machinery, Electrical Engineering (AMMEE 2017)
PB  - Atlantis Press
SP  - 406
EP  - 412
SN  - 2352-5401
UR  - https://doi.org/10.2991/ammee-17.2017.77
DO  - 10.2991/ammee-17.2017.77
ID  - Ren2017/06
ER  -