Abstract

This paper presents a multi-resolution masks based pattern matching method for person identification. The system is commenced with the construction of multi-resolution mask cluster pyramid, where the mask size is chosen depending on the distance between two eyes, computed from the detected face. Experimental results show the effectiveness of the system with significantly higher precision, recall rates and matching probability comparing with conventional single resolution mask based person identification systems. This paper also presents a novel person to camera distance measuring system based on eye-distance. The distance between centers of two eyes (interocular distance) is used for measuring the person to camera distance. The variation in eye-distance (in pixels) with the changes in camera to person distance (in inches) is used to formulate the distance measuring system. Experimental results show the effectiveness of the distance measurement system with an average accuracy of 94.11%.

Key words: Single resolution mask, multi-resolution masks, person to camera distance, person identification.