Name
Abstract | ||
|---|---|---|
The presence of occlusions in facial images is inevitable in unconstrained scenarios. However recognizing occluded faces remains a partially solved problem in computer vision. In this contribution we propose a novel Bayesian technique inspired by psychophysical mechanisms relevant to face recognition to address the facial occlusion problem. For some individuals certain facial regions, e.g. features comprising of some of the upper face, might be more discriminative than the rest of the features in the face. For others, it might be the features over the mid face and some of the lower face that are important. The proposed approach in this paper, will allow for such a psychophysical analysis to be factored into the recognition process. We have discovered and modeled similarity mappings that exist in facial domains by means of Bayesian Networks. The model can efficiently learn and exploit these mappings from the facial domain and hence capable of tackling uncertainties caused by occlusions. The proposed technique shows improved recognition rates over state of the art techniques. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.patrec.2012.05.003 | Pattern Recognition Letters |
Keywords | Field | DocType |
occluded face,upper face,facial occlusion problem,lower face,recognition rate,recognition process,psychophysically inspired similarity map,facial image,mid face,facial domain,individuals certain facial region,algorithms,familiar,saliency,face recognition,bayesian network,machine learning,representation,identification | Computer vision,Facial recognition system,Face hallucination,Pattern recognition,Three-dimensional face recognition,Salience (neuroscience),Bayesian network,Artificial intelligence,Face detection,Discriminative model,Mathematics,Bayesian probability | Journal |
Volume | Issue | ISSN |
34 | 8 | 0167-8655 |
Citations | PageRank | References |
8 | 0.47 | 23 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ibrahim Venkat | 1 | 70 | 14.37 |
| Ahamad Tajudin Khader | 2 | 683 | 40.71 |
| K. G. Subramanian | 3 | 339 | 59.27 |
| Philippe De Wilde | 4 | 192 | 23.86 |