A Method Based on Moment Invariants and Sparse Representation for 3D Face Recognition
This paper presents a moment invariants based three-dimensional face recognition method under sparse representation framework. An improved moment invariants descriptor is constructed and the discriminative ability in face recognition is validated on NPU3D and FRAV database. A series of partial faces are obtained by segmenting each face model according to the geodesic distance from nose middle point. Proposed moments invariants is computed and stacked as the feature of each face model. Finally, sparse representation is used in the classification step. The result on GavabDB shows that this method is very promising, compared with ICP baseline.
moment invariants sparse representation 3-D face recognition NPU3D face database
Chao Zhang Yanning Zhang
Shaanxi Provincial Key Laboratory of Speech & Image Information Processing, School of Computer Science, Northwestern Polytechnical University, Xian China, 710129
国际会议
重庆
英文
116-120
2011-01-21（万方平台首次上网日期，不代表论文的发表时间）