Title :
A rotation and location invariant face identification and localization with or without occlusion using modified RBFN
Author :
Bhakta, Dhananjoy ; Sarker, Goutam
Author_Institution :
Comput. Sci. & Eng. Dept., NIT Durgapur, Durgapur, India
Abstract :
This paper presents a new modified Radial Basis Function Network (RBFN) for identifying and localizing faces with or without occlusion for single images as well as for multiple image frame. The present method of facial identification is completely rotation and location invariant in the image frame. The technique of using the modified RBFN to perform learning of the different facial images and subsequent identification and location invariant localization of the clear, rotated and occluded faces is efficient, effective and fast. Also the identification rate of faces in single and multi-frame is quiet moderate.
Keywords :
face recognition; learning (artificial intelligence); radial basis function networks; facial images; image frame; location invariant face identification; location invariant face localization; machine learning; modified RBFN; modified radial basis function network; multiple image frame; occlusion; rotation invariant face identification; rotation invariant face localization; Clustering algorithms; Conferences; Databases; Face; Neural networks; Training; Vectors; ANN; BP Networks; Face Identification; Face Localization; Identification Rate; Machine Learning; OCA; RBFN;
Conference_Titel :
Image Information Processing (ICIIP), 2013 IEEE Second International Conference on
Conference_Location :
Shimla
Print_ISBN :
978-1-4673-6099-9
DOI :
10.1109/ICIIP.2013.6707649