Abstract
In this paper, we present a technique for semantic video segmentation. Our technique uses a combination of low-level features and high-level rules which organizes the video into scenes, shots and key-frames. Features in color domain is calculated and utilized for detecting the key-frames and estimating the similarity between shots. By applying a set of high-level rules, similar shots are merged and the scene boundaries are determined. Finally, a likelihood function is designed for improving the accuracy of scene boundary results. Experimental results from several Hollywood movies have demonstrated and show a better performance of both precision and recall has been achieved comparing with other existing works.
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.
