DocumentCode
3278700
Title
Moving human tracking algorithm based on partial Hausdorff distance
Author
Li, Li ; Xu Ji-ning
Author_Institution
Coll. of Mech. & Electr. Eng., North China Univ. of Technol., Beijing, China
fYear
2011
fDate
15-17 April 2011
Firstpage
5110
Lastpage
5113
Abstract
In order to realize accurate and fast tracking moving human, a moving human tracking algorithm based on partial Hausdorff distance is presented. This algorithm adopts Gaussian mixture distribution to model background of each pixel and background subtraction to detect moving regions. Shadow elimination and after treatment of moving regions provide moving human regions. Kalman filter is used to predict the position of tracking target in the next frame. Partial Hausdorff distance calculation is used to realize exact match, and the purpose of accurate and efficient tracking moving human can be reached. The experimental results show that the algorithm can continually track moving human accurately and fast despite occlusions and other moving object interference.
Keywords
Gaussian processes; Kalman filters; object detection; object tracking; target tracking; Gaussian mixture distribution; Kalman filter; moving human tracking algorithm; moving region detection; partial Hausdorff distance; shadow elimination; target tracking; Computer vision; Conferences; Humans; Kalman filters; Niobium; Prediction algorithms; Target tracking; Hausdorff distance; moving human detection; target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Electric Information and Control Engineering (ICEICE), 2011 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-8036-4
Type
conf
DOI
10.1109/ICEICE.2011.5777536
Filename
5777536
Link To Document