IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method for Robust Nose Tip Location across Pose Variety in 3D Face Data
CAR '09 Proceedings of the 2009 International Asia Conference on Informatics in Control, Automation and Robotics
3-D face detection, landmark localization, and registration using a point distribution model
IEEE Transactions on Multimedia
Point-pair descriptors for 3D facial landmark localisation
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Automatic 3d face feature points extraction with spin images
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
2D and 3d multimodal hybrid face recognition
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
3D facial feature localization for registration
MRCS'06 Proceedings of the 2006 international conference on Multimedia Content Representation, Classification and Security
3D facial landmark localization via a local surface descriptor HoSNI
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
ACM SIGAPP Applied Computing Review
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As interest in 3D face recognition increases the importance of the initial alignment problem does as well. In this paper we present a method utilizing the registered 2D color and range image of a face to automatically identify the eyes, nose, and mouth. These features are important to initially align faces in both standard 2D and 3D face recognition algorithms. For our algorithm to run as fast as possible, we focus on the 2D color information. This allows the algorithm to run in approximately 4 seconds on a 640X480 image with registered range data. On a database of 1,500 images the algorithm achieved a facial feature detection rate of 99.6% with 0.4% of the images skipped due to hair obstruction of the face.