Title :
Robust upper body detection in unconstrained posture
Author :
Li, Diping ; Zou, Beiji
Author_Institution :
Sch. of Inf. Sci. & Eng., Central South Univ., Changsha, China
Abstract :
This paper presents an efficient approach to detecting upper body in unconstrained posture based on Shape Context and Histograms of Orient Gradients. The method contains two steps. Shape context matching is used to get the candidates of upper bodies in the images at first, and then validation of each candidate is performed by using the Histograms of Orient Gradients. The method has two advantages, comparing with existing body detection methods. One is that it can detect upper bodies in all kinds of postures other than upright standing posture, and the other is that it significantly speeds up the computation.
Keywords :
gradient methods; image matching; image motion analysis; shape recognition; statistical analysis; orient gradient histograms; robust upper body detection; shape context matching; unconstrained posture; Computer vision; Context; Histograms; Humans; Pattern recognition; Shape; Support vector machines; HOG; Shape Context; image registration; upper body detection;
Conference_Titel :
Multimedia Technology (ICMT), 2011 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-61284-771-9
DOI :
10.1109/ICMT.2011.6002221