Extraction of regions of interest from face images using cellular analysis
COMPUTE '08 Proceedings of the 1st Bangalore Annual Compute Conference
Facial Feature Extraction and Change Analysis Using Photometric Stereo
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
Head Pose Estimation from Passive Stereo Images
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Human-computer interaction system based on nose tracking
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
A robust method for nose detection under various conditions
ICCVG'10 Proceedings of the 2010 international conference on Computer vision and graphics: Part I
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FRGC aims to develop algorithms that make use of the high quality images in the face database. The algorithms in this paper have been developed with this in view. We present methods to estimate pose using multi-view classifiers. Based on the knowledge of pose and face geometry a region of interest of possible eye locations is found. An adaptive thresholding is used to pick out the darkest pixels in this region, which forms the eye region. Using this information region of interest of nose location is formed. A gradient operator is used to obtain the edges in this region. Histogram thresholding is used to find the nose in this region. Lines are drawn joining the center points of each of the regions. Perpendicular is drawn to the line joining the eye centers. Based on the slopes of these lines the pose angle is determined. The FRGC version 2 experiment number 4 image set is used to test the eye location algorithm while the nose location and pose angle methods are tested on version 1 image set.