Name
Abstract | ||
|---|---|---|
Face verification in an uncontrolled environment is a challenging task due to the possibility of large variations in pose, illumination, expression, occlusion, age, scale, and misalignment. To account for these intra-personal settings, this paper proposes a sparsity sharing embedding (SSE) method for face verification that takes into account a pair of input faces under different settings. The proposed SSE method measures the distance between two input faces ${\mathbf x}_A$ and ${\mathbf x}_B$ under intra-personal settings sA and sB in two steps: 1) in the association step, ${\mathbf x}_A$ and ${\mathbf x}_B$ is represented in terms of a reconstructive weight vector and identity under settings sA and sB, respectively, from the generic identity dataset; 2) in the prediction step, the associated faces are replaced by embedding vectors that conserve their identity but are embedded to preserve the inter-personal structures of the intra-personal settings. Experiments on a MultiPIE dataset show that the SSE method performs better than the AP model in terms of the verification rate. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-37444-9_49 | ACCV |
Keywords | Field | DocType |
intra-personal setting,associated face,intra-personal settings sa,generic identity dataset,verification rate,proposed sse method,sse method,settings sa,sparsity sharing,multipie dataset show,face verification | Face verification,Facial recognition system,Embedding,Pattern recognition,Computer science,Sparse approximation,Local binary patterns,Weight,Artificial intelligence | Conference |
Citations | PageRank | References |
0 | 0.34 | 20 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Donghoon Lee | 1 | 151 | 22.04 |
| Park, Hyunsin | 2 | 11 | 2.69 |
| Junyoung Chung | 3 | 1115 | 39.41 |
| Youngook Song | 4 | 0 | 0.34 |
| Chang D. Yoo | 5 | 375 | 45.88 |