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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
