Title :
Abandoned object detection in complicated environments
Author :
Muchtar, Kahlil ; Chih-Yang Lin ; Li-Wei Kang ; Chia-Hung Yeh
Author_Institution :
Dept. of Electr. Eng., Nat. Sun Yat-sen Univ., Kaohsiung, Taiwan
fDate :
Oct. 29 2013-Nov. 1 2013
Abstract :
In video surveillance, tracking-based approaches are very popular especially for detecting abandoned objects in public areas. Once the object has been tracked, the object status can be further classified as removed or abandoned. However, some shortcomings were found on tracking-based approaches, e.g. illumination changes and occlusion. Therefore, in this paper, an alternative approach to detect abandoned objects is proposed by incorporating background modeling and Markov model. In addition the shadow removal is employed to rectify detected objects and obtain more accurate results. The experimental results show that the proposed scheme is better than other methods in terms of accuracy and correctness.
Keywords :
Markov processes; image classification; object detection; object tracking; public administration; video surveillance; Markov model; abandoned object detection; background modeling; complicated environments; object status classification; object tracking-based approach; public areas; video surveillance; Computational modeling; Educational institutions; Gaussian distribution; Object detection; Real-time systems; Robustness; Surveillance;
Conference_Titel :
Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2013 Asia-Pacific
Conference_Location :
Kaohsiung
DOI :
10.1109/APSIPA.2013.6694206