| Paper: | TP-P7.12 |
| Session: | Biometrics IV: Face Recognition |
| Time: | Tuesday, September 18, 14:30 - 17:10 |
| Presentation: |
Poster
|
| Title: |
LOCATING NOSETIPS AND ESTIMATING HEAD POSE IN IMAGES BY TENSORPOSES |
| Authors: |
Jilin Tu; University of Illinois at Urbana-Champaign | | |
| | Thomas Huang; University of Illinois at Urbana-Champaign | | |
| Abstract: |
This paper introduces a head pose estimation system that localizes nose-tip of the faces and estimate head poses in images simultaneously. After the nose-tip in the training data are manually labeled, the appearance variation caused by head pose changes is characterized by tensor model. Given images with unknown head pose and nose-tip location, the nose-tip of the face is localized in a coarse-to-fine fashion, and the head pose can be estimated simultaneously. We evaluated our system on the Pointing'04 head pose image database with $50\%$ of the data as training set and the rest as testing set. With the nose-tip location known, our head pose estimators can achieve $94\%$ head pose classification accuracy(within $\pm 15^o$). With nose-tip unknown, we achieves 85\% nose-tip localization accuracy(within 3 pixels from the ground truth), and $81\%$ head pose classification accuracy(within $\pm 15^o$). |
