Name
Abstract | ||
|---|---|---|
Face is the most frequently used biometric trait after fingerprint. Its applicability made it popular in different areas such as Human Robot Interaction (HRI), Security Authentication, and Surveillance to name a few. Face recognition concept is based on two major blocks, training and testing. Usually training is done offline while testing is performed in real time scenario. As the size of the database increases, the recognition rate (time taken by system to recognize) increases. The rate of recognition is directly proportional to the size of the database and the dimension of the images. Human faces have the vertical symmetry; hence we utilized this feature and proposed a half way face recognition approach. Experimental verification on both the full faces and the half faces shows that half faces are also sufficient for recognizing the person. For verifying the efficiency of the approach, we have applied PCA (Principle Component Analysis) on both, the full faces and half faces, and have found that in both the cases, accuracy is almost same. But the recognition rate of half faces is just the half of the full faces. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2393216.2393308 | CCSEIT |
Keywords | Field | DocType |
security authentication,full face,human robot interaction,human face,facial symmetry,recognition rate,face recognition concept,database increase,face recognition approach,principle component analysis,real time scenario,pca,face recognition | Computer vision,Facial recognition system,Face hallucination,Authentication,Three-dimensional face recognition,Computer science,Fingerprint,Artificial intelligence,Face detection,Biometrics,Human–robot interaction | Conference |
Citations | PageRank | References |
2 | 0.39 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Avinash Kumar Singh | 1 | 31 | 13.77 |
| G. C. Nandi | 2 | 71 | 10.28 |