Title :
Face recognition through regional weight estimation
Author :
Yule, Daniel ; Chen, Liang
Author_Institution :
Dept. of Comput. Sci., Univ. of Northern British Columbia, Prince George, BC, Canada
Abstract :
Face recognition has become a very important field of AI, with many competing techniques, both holistic and local. Recently, a new framework for embedding holistic face recognition algorithms into a regional voting approach, has been shown to be a very stable and accurate mechanism for face recognition. A new system is proposed, which extends the regional voting concept and adds weights to each region. Several techniques for estimating the weights are discussed. The system is shown to outperform several other leading face recognition algorithms.
Keywords :
computer vision; embedded systems; face recognition; learning (artificial intelligence); AI field; embedding holistic face recognition algorithm; regional voting concept; regional weight estimation; weight estimation; Accuracy; Algorithm design and analysis; Error analysis; Face; Face recognition; Probes; Training; Face Recognition; Machine Learning; Machine Vision; Object Recognition;
Conference_Titel :
Image Processing (ICIP), 2011 18th IEEE International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4577-1304-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2011.6115801