Name
Abstract | ||
|---|---|---|
In this paper a novel algorithm to solve the problem of automatic face recognition is presented. The novelty of the algorithm is the ability to combine the computer vision tasks with Particle Swarm Optimization (PSO) to improve the execution time and to obtain better recognition results. The crucial stage of a typical system of face recognition is improved by using a fitness function to measure the similarity of an input face compared with a database of faces. The use of the fitness function helps to obtain more accurate results in a faster way. The results obtained are excellent even when the system was tested in uncontrolled environments. A comparison of the results obtained with the algorithm without PSO versus the algorithm using PSO is also presented. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/SITIS.2009.17 | Signal-Image Technology & Internet-Based Systems |
Keywords | Field | DocType |
computer vision task,particle swarm optimization,novel evolutionary face recognition,face recognition,automatic face recognition,fitness function,typical system,better recognition result,crucial stage,novel algorithm,accurate result,algorithm design and analysis,face,evolutionary algorithm,evolutionary computing,eigenfaces,image recognition,evolutionary computation,computer vision | Eigenface,Evolutionary algorithm,Computer science,Artificial intelligence,Particle swarm optimization,Computer vision,Facial recognition system,Algorithm design,Pattern recognition,Evolutionary computation,Algorithm,Fitness function,Novelty | Conference |
ISBN | Citations | PageRank |
978-0-7695-3959-1 | 1 | 0.34 |
References | Authors | |
12 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Osslan Osiris Vergara Villegas | 1 | 15 | 6.40 |
| Mitzel Aviles Quintero | 2 | 1 | 0.34 |
| Vianey Guadalupe Cruz Sanchez | 3 | 4 | 1.11 |
| de Jesús Ochoa Domínguez, H. | 4 | 1 | 0.34 |