Automatic recommendation system of IPTV contents for baseball video

In this paper, we propose a system to analyze baseball videos for creating video annotation and recommendation. For video annotation, we treat the video segment between two pitch shots as a event. The caption is inferred to find categories of the event. A rule-based decision tree is used to classify...

Full description

Saved in:
Bibliographic Details
Published in2013 International Symposium on Intelligent Signal Processing and Communication Systems pp. 714 - 717
Main Authors Kai-Shun Lin, Kuei-Hong Lin, Kuo-Huang Chung
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2013
Subjects
content-based method
Decision trees
Engines
highlight event
History
Image color analysis
IPTV
recommendation systems
Servers
Sports equipment
Online AccessGet full text

Cover

More Information
Summary:In this paper, we propose a system to analyze baseball videos for creating video annotation and recommendation. For video annotation, we treat the video segment between two pitch shots as a event. The caption is inferred to find categories of the event. A rule-based decision tree is used to classify a event into four event categories. For video recommendation, users are recommended items that according to highlight events. They can browse their favorite events in a baseball video. The algorithm is tested on 68 events from US and Taiwan baseball video. All events are rated in a 1-to-5 rating scale. The highest average rating is 4.4.
DOI:10.1109/ISPACS.2013.6704642