Title :
Automatic and robust head pose estimation by block energy map
Author :
Wei Li ; Yan Huang ; Jingliang Peng
Author_Institution :
Sch. of Comput. Sci. & Technol., Shandong Univ., Jinan, China
Abstract :
It is a crucial problem to estimate head pose automatically and robustly in many visual applications. In order to solve this problem, we propose in this work a novel and simple face image descriptor (i.e., block energy map) and, based on which, complete schemes for automatic and robust head pose estimation using support vector regression and Gaussian processes regression, respectively. The proposed descriptor and schemes contrast with many of the previously published ones that rely on manual assistance to locate the face position in an input image and/or are sensitive to factors such as identity and misalignment. Experimental results demonstrate the superiority of the proposed descriptor and schemes.
Keywords :
Gaussian processes; pose estimation; regression analysis; support vector machines; Gaussian process regression; automatic robust head pose estimation; block energy map; simple face image descriptor; support vector regression; Estimation; Face; Ground penetrating radar; Magnetic heads; Robustness; Support vector machines; Gaussian processes regression (GPR); Head pose estimation; block energy map (BEM); support vector regression (SVR);
Conference_Titel :
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location :
Paris
DOI :
10.1109/ICIP.2014.7025679