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
Three-Dimensional Model Based Face Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Registration of point cloud data from a geometric optimization perspective
Proceedings of the 2004 Eurographics/ACM SIGGRAPH symposium on Geometry processing
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In this paper, we present a novel algorithm for 3D face recognition that is robust to the rotations and translations of the face models. Based on the Iterative Closest Point algorithm, a template based registration strategy is proposed for data normalization. Back-Propagation neural networks are then constructed to perform recognition tasks. The proposed algorithm is general purpose and can be applied for common 3D object recognitions. Experimental results illustrate that the algorithm is effective and robust.