This paper is concerned with the template-based face recognition from robot camera images with illumination and distance variations. The approaches used in this paper consist of Eigenface, Fisherface, and Icaface which are the most representative recognition techniques frequently used in conjunction with face recognition. These approaches are based on a popular unsupervised and supervised statical technique that supports finding useful image representations, respectively. Thus we focus on the performance comparison from robot camera images with unwanted variations. The comprehensive experiments are completed for a databases with illumination and distance variations.

• 반규대 | Kyu-Dae Ban
• 곽근창 | Keun-Chang Kwak
• 지수영 | Su-Young Chi
• 정연구 | Yun-Koo Chung