Video shot boundary detection based on candidate segment selection and transition pattern analysis

Conference proceedings article

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Publication Details

Author list: Tippaya S., Sitjongsataporn S., Tan T., Chamnongthai K., Khan M.

Publisher: Hindawi

Publication year: 2015

Volume number: 2015-September

Start page: 1025

End page: 1029

Number of pages: 5

ISBN: 9781479980581; 9781479980581

ISSN: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961351357&doi=10.1109%2fICDSP.2015.7252033&partnerID=40&md5=be5aa57f99536adf1009d33f0d8f74f8

Languages: English-Great Britain (EN-GB)

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Abstract

Video shot boundary detection or shot segmentation is an integral part of semantic video analysis. The objective of this process is to automatically detect the boundary region in video that further segment the video into meaningful shot, scene and so on. Video frame feature representation therefore plays an important role in the process where it directly affects the overall performance of the system. The transition points between meaningful scenes can be emphasised by the extracted features. In this paper, a combination of global and local feature descriptors is implemented to represent the temporal characteristic in video. Motivated by computational efficiency and practical implementation, a video shot boundary detection scheme using adaptive thresholding is proposed. Candidate segment selection and transition pattern analysis are implemented by the dissimilarity score between video frames. The performance evaluation is constructed on a golf video dataset using the precision and recall performance measures. ฉ 2015 IEEE.

Keywords

adaptive thresholding, golf video analysis, speeded up robust features, Video shot boundary detection