DocumentCode
231708
Title
Memory-based codebook model for real-time object detection
Author
Xiaoran Niu ; Yanjiang Wang ; Yujuan Qi
Author_Institution
Coll. of Inf. & Control Eng., China Univ. of Pet., Qingdao, China
fYear
2014
fDate
19-23 Oct. 2014
Firstpage
913
Lastpage
917
Abstract
In order to improve codebook (CB) model by reducing its training procedure, we introduce the human memory mechanism into CB and a memory-based codebook model is proposed. The proposed method extracts both the background and foreground into codewords and training procedure is no longer necessary. Experimental results show that our method improves the processing speed and achieves better performance in handling background variations. In addition, the proposed method can be applied in real-time monitoring.
Keywords
computer vision; feature extraction; image coding; object detection; CB model; background extraction; background variations; foreground extraction; human memory mechanism; memory-based codebook model; real-time monitoring; real-time object detection; training procedure; Adaptation models; Computational modeling; Monitoring; Object detection; Real-time systems; Training; Background modeling; codebook model; foreground modeling; human memory; object detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing (ICSP), 2014 12th International Conference on
Conference_Location
Hangzhou
ISSN
2164-5221
Print_ISBN
978-1-4799-2188-1
Type
conf
DOI
10.1109/ICOSP.2014.7015137
Filename
7015137
Link To Document