Complete face logs for video sequences using face quality measures

Abstract

Reducing a video sequence containing a human's face to just a few high-quality face images (Face Log) has a considerable importance in applications related to face processing. This face log can be considered as a concise representation of the video sequence. Producing such a complete face log is the focus of this paper. To decide about the presence of each face in the face log, their quality using four facial features is assessed. Relative quality scores are assigned to these features and then combined into one quality score for each face using a fuzzy inference engine. The authors introduce a method for choosing the M-best images for construction of the face logs. These best images are selected as local maxima in different temporal periods of the sequence. The introduced system has been evaluated using four different datasets including still images and video sequences under various conditions. Experimental results show the success of the system in finding the best face images and using these for producing complete face logs.