Title :
Head pose estimation: Classification or regression?
Author :
Guo, Guodong ; Fu, Yun ; Dyer, Charles R. ; Huang, Thomas S.
Author_Institution :
Comput. Sci., NCCU, Durham, NC, USA
Abstract :
Head pose estimation has many useful applications in practice. How to estimate the head pose automatically and robustly is still a challenging problem. In pose estimation, different pose angles can be used as regression values or viewed as different class labels. Thus a question is raised in our study: which is proper for pose estimation - classification or regression? We investigate representative classification and regression methods on the same problem to see any difference. A method that combines regression and classification approaches is also examined. Preliminary experiments show some interesting results which might prompt further exploration of related issues in pose estimation.
Keywords :
image classification; pose estimation; regression analysis; head pose estimation; regression method; representative classification; Application software; Computer science; Databases; Face recognition; Humans; Magnetic heads; Robustness; Support vector machine classification; Support vector machines; Training data;
Conference_Titel :
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
978-1-4244-2174-9
Electronic_ISBN :
1051-4651
DOI :
10.1109/ICPR.2008.4761081