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
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;
Conference_Titel :
Electric Information and Control Engineering (ICEICE), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-8036-4
DOI :
10.1109/ICEICE.2011.5777536