DocumentCode
1775493
Title
Automated image tracking based on the CAMSHIFT algorithm with adaboost and target trajectory and size estimation
Author
Chi-Juang Hsieh ; Kai-Yew Lum
Author_Institution
Dept. of Electr. Eng., Nat. Chi Nan Univ., Nantou, Taiwan
fYear
2014
fDate
18-20 June 2014
Firstpage
918
Lastpage
923
Abstract
In order to overcome a shortcoming of traditional CAMSHIFT which requires manual target designation and object color similarity between frames, this paper proposes an image tracking algorithm by a combination of CAMSHIFT with Adaboost object detection and the Kalman estimator. The proposed method alleviates loss-of-track problems caused by accelerating target motion and color noise. Robustness against occlusion is also improved, while the number of iterations that CAMSHIFT requires is reduced.
Keywords
learning (artificial intelligence); object detection; target tracking; Adaboost object detection; CAMSHIFT algorithm; Kalman estimator; automated image tracking algorithm; color noise; frames; object color similarity; occlusion; robustness; size estimation; target designation; target motion; target trajectory; Acceleration; Face; Image color analysis; Interference; Kalman filters; Object detection; Target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Control & Automation (ICCA), 11th IEEE International Conference on
Conference_Location
Taichung
Type
conf
DOI
10.1109/ICCA.2014.6871044
Filename
6871044
Link To Document