Title :
Locating Nosetips and Estimating Head Pose in Images by Tensorposes
Author :
Tu, Jilin ; Huang, Thomas
Author_Institution :
Illinois Univ., Urbana
fDate :
Sept. 16 2007-Oct. 19 2007
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 provided, our head pose estimators can achieve 94% head pose classification accuracy(within plusmn15deg). With nose-tip automatically localized, we achieves 85% nose-tip localization accuracy(within 3 pixels from the ground truth), and 81% head pose classification accuracy (within plusmn15deg).
Keywords :
face recognition; human computer interaction; image classification; pose estimation; tensors; face recognition; head pose estimation system; human computer interaction; image classification; image database; nose-tip localization; tensor model; Eyes; Face detection; Head; Humans; Image databases; Image resolution; Nose; Tensile stress; Testing; Training data; Head Pose; Tensor; nose-tip localization; pointing04;
Conference_Titel :
Image Processing, 2007. ICIP 2007. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-1437-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2007.4380067