Minimum resolution for human face detection and identification

摘要

Abstract: Our goal is to build an automated system for face recognition. Such a system for a realistic application is likely to have thousands, possibly millions of faces. Hence, it is essential to have a compact representation for a face. So an important issue is the minimum spatial and grayscale resolutions necessary for a pattern to be detected as a face and then identified. Several experiments were performed to estimate these limits using a collection of 64 faces imaged under very different conditions. All experiments were performed using human observers. The results indicate that there is enough information in 32 $MUL 32 $MUL 4 bpp images for human eyes to detect and identify the faces. Thus an automated system could represent a face using only 512 bytes.!