Face detection and recognition using low quality video cameras
Date of Publication
2008
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Computer Science
College
College of Computer Studies
Department/Unit
Computer Science
Thesis Adviser
Rigan P. Ap-apid
Defense Panel Member
Joel P. Ilao
Conrado D. Ruiz, Jr.
Abstract/Summary
Face detection and recognition are applications of image processing and analysis. Though several system have already been implemented to detect and recognize faces from image sequences, there are still problems being faced like having to recognize through a real surveillance. This is mostly because of the poor quality of images and diminutive size of the faces.
In this paper, the proponents present a simple and effective method to detect faces in low-quality video by using multi-module integration. The proponents combine skin detection module, template matching, and local face region analysis method into a single face detection system. In addition to that, a recognition module based on template matching using Pearson's Linear Correlation Coefficient is also discussed. Our results show that the combined face detection algorithm works fast and accurate in detecting faces with respect to the poor quality and sizes of faces."
Abstract Format
html
Language
English
Format
Accession Number
TU14644
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Recommended Citation
Blancas, K. T., Chan, A. T., Chua, P. D., & Yeung, W. S. (2008). Face detection and recognition using low quality video cameras. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/14433