Title
A Multi-Level Framework For Video Shot Structuring
Abstract
Video shots provide the most basic meaningful segments for video analysis and understanding. In this paper, we present a detection and classification framework for the video shot segmentation in a coarse-to-fine fashion. The initial transitions are detected from a sub-sampled video space. These coarse segments are later refined in the original video space with the technique of illumination artifacts removal and transition finalization. The transition type (abrupt or gradual) are finally determined by exploiting the hislogram intersection plot. The proposed method has been tested on a large amount of videos, which contain a variety of types of shot transitions. Accurate and competitive results have been obtained. © Springer-Verlag Berlin Heidelberg 2005.
Publication Date
12-1-2005
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
3656 LNCS
Number of Pages
167-173
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/11559573_21
Copyright Status
Unknown
Socpus ID
33645978971 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/33645978971
STARS Citation
Zhai, Yun and Shah, Mubarak, "A Multi-Level Framework For Video Shot Structuring" (2005). Scopus Export 2000s. 3344.
https://stars.library.ucf.edu/scopus2000/3344