Name
Abstract | ||
|---|---|---|
In this paper, we propose a memetic based framework called Optimized Symmetric Partial Facegraphs (OSPF) to recognize faces prone to adverse conditions such as facial occlusions, expression and illumination variations. Faces are initially segmented into facial components and optimal landmarks are automatically generated by exploiting the bilateral symmetrical property of human faces. The proposed approach combines an improved harmony search algorithm and an intelligent single particle optimizer to take advantage of their global and local search capabilities. Basically, the hybridization version aids to compute the optimal landmarks. These landmarks further serve as the building blocks to intuitively construct the partial facegraphs. The efficiency of the proposed approach has been investigated in addressing the facial occlusion problem when only one exemplar face image per subject is available using comprehensive experimental validations. The proposed approach yields improved recognition rates when compared to recent state-of-the-art techniques. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.ins.2017.11.013 | Information Sciences |
Keywords | Field | DocType |
Face recognition,Facial occlusion,Symmetric partial facegraphs,Harmony search algorithm,Intelligent single particle optimizer | Open Shortest Path First,Computer vision,Facial recognition system,Adverse conditions,Harmony search,Artificial intelligence,Local search (optimization),Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
429 | C | 0020-0255 |
Citations | PageRank | References |
0 | 0.34 | 35 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Badr Mohammed Lahasan | 1 | 13 | 1.55 |
| Syaheerah Lebai Lutfi | 2 | 23 | 3.92 |
| Ibrahim Venkat | 3 | 70 | 14.37 |
| Mohammed Azmi Al-Betar | 4 | 620 | 43.69 |
| Rubén San-Segundo-Hernández | 5 | 173 | 29.60 |