Title :
Head pose estimation using view based eigenspaces
Author :
Srinivasan, Sujith ; Boyer, Kim L.
Author_Institution :
Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
Abstract :
View based eigenspaces can improve the performance of face recognition algorithms. In this work, we demonstrate their use in head pose estimation from head and shoulders video sequences. Our method compares the projected energies of the test image in multiple eigenspaces. We also demonstrate that very few eigenspaces are necessary for a rough estimate of head pose. The method is robust and computationally inexpensive.
Keywords :
eigenvalues and eigenfunctions; face recognition; image sequences; face recognition algorithms; head pose estimation; head shoulders video sequences; multiple eigenspaces; projected test image energies; view based eigenspaces; Face detection; Face recognition; Facial features; Lighting; Magnetic heads; Principal component analysis; Robustness; Signal analysis; Testing; Video sequences;
Conference_Titel :
Pattern Recognition, 2002. Proceedings. 16th International Conference on
Print_ISBN :
0-7695-1695-X
DOI :
10.1109/ICPR.2002.1047456