Sports video clustering
Date of Publication
2005
Document Type
Master's Thesis
Degree Name
Master of Science in Computer Science
College
College of Computer Studies
Department/Unit
Computer Science
Thesis Adviser
Rigan P. Ap-apid
Defense Panel Chair
Conrado D. Ruiz, Jr.
Defense Panel Member
Jose Ronello Bartolome
Alexis Pantola
Abstract/Summary
Video browsing has become more and more challenging over the past couple of years due to increased digital video availability. Without efficient indexing and organization, searching for videos over a huge media library poses a real problem. The goal of this research is to use clustering algorithms to group similar sports videos based on color and camera motion features. Sports genre is suitable for clustering since most sports videos have color and camera motion features that serve as important visual cues and can be used to identify them. A statistical method for combining color and camera motion features for clustering will also be developed. Once the sports videos have been clustered according to the similarity of their features, video retrieval can be done directly on a particular cluster, thus improving retrieval performance.
Abstract Format
html
Language
English
Format
Accession Number
TG03939; CDTG003939
Shelf Location
Archives, The Learning Commons, 12F Henry Sy Sr. Hall
Physical Description
1 v. (various foliations) ; 28 cm. + 1 computer optical disc.
Keywords
Video; Sports; Cluster analysis--Computer programs; Cluster set theory
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Recommended Citation
Ng, B. S. (2005). Sports video clustering. Retrieved from https://animorepository.dlsu.edu.ph/etd_masteral/3307