A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
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International Journal of Computer Vision
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FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
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FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Expression-invariant 3D face recognition
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Face authentication based on multiple profiles extracted from range data
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
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MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
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ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Efficient 3D face recognition handling facial expression and hair occlusion
Image and Vision Computing
Hi4D-ADSIP 3-D dynamic facial articulation database
Image and Vision Computing
Adaptive registration for occlusion robust 3d face recognition
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Computer Vision and Image Understanding
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This paper investigates facial expression effects in face recognition from 3D shape using partial ICP. The partial ICP method could implicitly and dynamically extract the rigid parts of facial surface by selecting a part of nearest points pairs to calculate dissimilarity measure during registration of facial surfaces. The method is expected to be able to get much better performance than other methods in 3D face recognition under expression variation for its dynamic extraction of rigid parts of facial surface at the same time of matching. We also present an effective method for coarse alignment of facial shape, which is fully automatic. Experiments on 3D face database of 360 models with 40 subjects, 9 scans with four different kinds of expression for each subject, show partial ICP is very promising, compared with PCA baseline.