Name
Title | ||
|---|---|---|
Gait recognition and micro-expression recognition based on maximum margin projection with tensor representation |
Abstract | ||
|---|---|---|
We contribute, through this paper, to design a novel algorithm called maximum margin projection with tensor representation (MMPTR). This algorithm is able to recognize gait and micro-expression represented as third-order tensors. Through maximizing the inter-class Laplacian scatter and minimizing the intra-class Laplacian scatter, MMPTR can seek a tensor-to-tensor projection that directly extracts discriminative and geometry-preserving features from the original tensorial data. We show the validity of MMPTR through extensive experiments on the CASIA(B) gait database, TUM GAID gait database, and CASME micro-expression database. The proposed MMPTR generally obtains higher accuracy than MPCA, GTDA as well as state-of-the-art DTSA algorithm. Experimental results included in this paper suggest that MMPTR is especially effective in such tensorial object recognition tasks. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s00521-015-2031-8 | Neural Computing and Applications |
Keywords | Field | DocType |
Maximum margin projection with tensor representation (MMPTR), Dimensionality reduction, Gait recognition, Micro-expression recognition | Dimensionality reduction,Gait,Tensor,Artificial intelligence,Discriminative model,Tensor representation,Computer vision,Facial expression recognition,Pattern recognition,Mathematics,Machine learning,Cognitive neuroscience of visual object recognition,Laplace operator | Journal |
Volume | Issue | ISSN |
27 | 8 | 1433-3058 |
Citations | PageRank | References |
19 | 0.61 | 36 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xianye Ben | 1 | 131 | 10.56 |
| peng zhang | 2 | 19 | 0.61 |
| Rui Yan | 3 | 88 | 5.22 |
| mingqiang yang | 4 | 19 | 0.61 |
| guodong ge | 5 | 19 | 0.61 |