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

Print

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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