3D human face recognition using point signature
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...
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Published in | 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2000) pp. 233 - 238 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
2000
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Subjects | |
Online Access | Get full text |
ISBN | 0769505805 9780769505800 |
DOI | 10.1109/AFGR.2000.840640 |
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Abstract | 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. |
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AbstractList | 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. |
Author | Chin-Seng Chua Yeong-Khing Ho Feng Han |
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Keywords | Three dimensional model Human face Face recognition Similarity Image processing Free form Facies Free surface Pattern recognition Indexing |
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PublicationTitle | 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2000) |
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Snippet | 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... |
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SubjectTerms | Applied sciences Artificial intelligence Color Computer science; control theory; systems Electrical capacitance tomography Exact sciences and technology Face recognition Humans Indexing Object recognition Pattern recognition. Digital image processing. Computational geometry Read only memory Shape Surface treatment Testing |
Title | 3D human face recognition using point signature |
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