Paper Info
Title
A spatio-temporal pyramid matching for video retrieval
Abstract
An efficient video retrieval system is essential to search relevant video contents from a large set of video clips, which typically contain several heterogeneous video clips to match with. In this paper, we introduce a content-based video matching system that finds the most relevant video segments from video database for a given query video clip. Finding relevant video clips is not a trivial task, because objects in a video clip can constantly move over time. To perform this task efficiently, we propose a novel video matching called Spatio-Temporal Pyramid Matching (STPM). Considering features of objects in 2D space and time, STPM recursively divides a video clip into a 3D spatio-temporal pyramidal space and compares the features in different resolutions. In order to improve the retrieval performance, we consider both static and dynamic features of objects. We also provide a sufficient condition in which the matching can get the additional benefit from temporal information. The experimental results show that our STPM performs better than the other video matching methods.
Year
DOI
Venue
2013
10.1016/j.cviu.2013.02.003
Computer Vision and Image Understanding
Keywords
Field
DocType
relevant video segment,video clip,novel video matching,spatio-temporal pyramid,relevant video content,query video clip,efficient video retrieval system,heterogeneous video clip,video database,relevant video clip,content-based video
Computer vision,Block-matching algorithm,Video post-processing,Computer science,Motion compensation,Multiview Video Coding,Video tracking,Smacker video,Artificial intelligence,Pyramid,Video compression picture types
Journal
Volume
Issue
ISSN
117
6
1077-3142
Citations 
PageRank 
References 
9
0.54
41
Authors
4
Name
Order
Citations
PageRank
Jaesik Choi122021.38
Ziyu Wang237223.71
Sang-Chul Lee328724.04
Won J. Jeon41448.44