Name
Abstract | ||
|---|---|---|
Face and object recognition in uncontrolled scenarios due to pose and illumination variations, low resolution, etc. is a challenging research area. Here we propose a novel descriptor, Aligned Discriminative Pose Robust (ADPR) descriptor, for matching faces and objects across pose which is also robust to resolution and illumination variations. We generate virtual intermediate pose subspaces from training examples at a few poses and compute the alignment matrices of those subspaces with the frontal subspace. These matrices are then used to align the generated subspaces with the frontal one. An image is represented by a feature set obtained by projecting its low-level feature on these aligned subspaces and applying a discriminative transform. Finally, concatenating all the features we generate the ADPR descriptor. We perform experiments on face and object databases across pose, pose and resolution, and compare with state-of-the-art methods including deep learning approaches to show the effectiveness of our descriptor. |
Year | Venue | Keywords |
|---|---|---|
2017 | 2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | Face recognition, object recognition, pose, subspace interpolation, subspace alignment |
Field | DocType | ISSN |
Computer vision,3D single-object recognition,Pattern recognition,Three-dimensional face recognition,Subspace topology,Computer science,Linear subspace,Artificial intelligence,Deep learning,Discriminative model,Image resolution,Cognitive neuroscience of visual object recognition | Conference | 1522-4880 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Soubhik Sanyal | 1 | 8 | 1.43 |
| Devraj Mandal | 2 | 44 | 5.42 |
| Soma Biswas | 3 | 3 | 3.41 |