Title :
Video object tracking based on position prediction guide CAMSHIFT
Author :
Ling, Yun ; Zhang, Jianxiang ; Xing, Jianguo
Author_Institution :
Coll. of Comput. & Inf. Eng., Zhejiang Gongshang Univ., Hangzhou, China
Abstract :
In this article, a novel algorithm-position prediction guide continuously adaptive mean shift procedure (CAMSHIFT)-is proposed for tracking objects in video sequences. CAMSHIFT is incorporated with the position prediction algorithm makes the scale adaptation of CAMSHIFT is improved, tracking efficiency increased and the computation complexity is reduced. Preliminary experimental results show the algorithm performs well. Meanwhile, the algorithm success in indicating new objects appeared; objects disappeared; objects collisions and the consistency of the objects in consecutive sequences.
Keywords :
computational complexity; navigation; object detection; tracking; video signal processing; CAMSHIFT; computation complexity; continuously adaptive mean shift procedure; object collisions; position prediction guide; scale adaptation; tracking efficiency; video object tracking; video sequences; CAMSHIFT; component; position prediction;
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6539-2
DOI :
10.1109/ICACTE.2010.5579041