Objects Detection and Recognition in Videos for Sequence Learning

Abstract

A key challenge to sequence learning for video comprehension is objects detection and localization in dynamic and real-time environment. This paper presents two methodological approaches to autonomous and generic object detection and localization in video sequences. Algorithms for both facial and non-facial object localization, as well as their integration, are developed. A set of experiments and case studies for practical video image processing is demonstrated for sequence learning. This work paves a way to sequence learning towards enhanced computer and robot vision technologies in applications of self-driving cars and real-time facial recognition.