Video object encoder using selective local-space support vector machines

Po Hsiang Tsai, Seun Jan, Hatice Gunes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Recently, Support Vector Machine (SVM) has been shown to be a good classifier; however, its large computational requirement prohibited its use in real time video processing applications. In this paper, a model is proposed that enables use of SVM in video applications. The proposed model allows selected image scales (of interest) to be encoded and classified more accurately by complex classifier such as SVM, whilst other image scales of less significance to be encoded and classified by simpler encoder/classifier. Experiment with video object encoding shows that the performance of the proposed model is comparable with other models, however with reduced computational requirements.

Original languageEnglish
Title of host publication2004 IEEE 6th Workshop on Multimedia Signal Processing
Pages427-429
Number of pages3
Publication statusPublished - 2004
Externally publishedYes
Event2004 IEEE 6th Workshop on Multimedia Signal Processing - Siena, Italy
Duration: 29 Sep 20041 Oct 2004

Publication series

Name2004 IEEE 6th Workshop on Multimedia Signal Processing

Conference

Conference2004 IEEE 6th Workshop on Multimedia Signal Processing
Country/TerritoryItaly
CitySiena
Period29/09/041/10/04

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