Abstract/Description
This paper proposes a face recognition scheme that enhances the correct face recognition rate as compared to conventional Principal Component Analysis (PCA). The proposed scheme, Sub-Holistic PCA (SH-PCA), was tested using ORL database and out performed PCA for all test scenarios. SH-PCA requires more computational power and memory as compared to PCA however it yields an improvement of 6% correct recognition on the complete ORL database of 400 images. The correct recognition rate for the complete ORL database is 90% for the SH-PCA technique.
Keywords
Face recognition, Principal component analysis, Image databases, Testing, Eigenvalues and eigenfunctions, Surveillance
Location
Crystal Ball Room A, Hotel Pearl Continental, Karachi, Pakistan
Session Theme
Poster Session A: Artificial Intelligence [AI-1]
Session Type
Poster Session
Session Chair
Dr. Arshad B. Siddiqui
Start Date
28-8-2005 11:15 AM
End Date
28-8-2005 11:35 AM
Recommended Citation
Khan, M. M., Javed, D. Y., & Anjum, M. A. (2005). Poster Session A: Face Recognition using Sub-Holistic PCA. International Conference on Information and Communication Technologies. Retrieved from https://ir.iba.edu.pk/icict/2005/2005/10
COinS
Poster Session A: Face Recognition using Sub-Holistic PCA
Crystal Ball Room A, Hotel Pearl Continental, Karachi, Pakistan
This paper proposes a face recognition scheme that enhances the correct face recognition rate as compared to conventional Principal Component Analysis (PCA). The proposed scheme, Sub-Holistic PCA (SH-PCA), was tested using ORL database and out performed PCA for all test scenarios. SH-PCA requires more computational power and memory as compared to PCA however it yields an improvement of 6% correct recognition on the complete ORL database of 400 images. The correct recognition rate for the complete ORL database is 90% for the SH-PCA technique.
