3D human face recognition using point signature 论文

摘要

We present a novel face recognition algorithm based on the point signature-a representation for free-form surfaces. We treat the face recognition problem as a non-rigid object recognition problem. The rigid parts of the face of one person are extracted after registering the range data sets of faces having different facial expressions. These rigid parts are used to create a model library for efficient indexing. For a test face, models are indexed from the library and the most appropriate models are ranked according to their similarity with the test face. Verification of each model face can be quickly and efficiently identified. Experimental results with range data involving six human subjects, each with four different facial expressions, have demonstrated the validity and effectiveness of our algorithm.