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Choi, Jaesik
Statistical Artificial Intelligence Lab
Research Interests
  • Artificial intelligence, machine learning, deep learning, robotics, automatic statistician, semantic segmentation, fault detection

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A spatio-temporal pyramid matching for video retrieval

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Title
A spatio-temporal pyramid matching for video retrieval
Author
Choi, JaesikWang, ZiyuLee, Sang-ChulJeon, Won J.
Keywords
High-activity videos; Pyramid matching; Query by video clip; Spatio-temporal pyramid matching; Sport videos; Video retrieval
Issue Date
2013-06
Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
Citation
COMPUTER VISION AND IMAGE UNDERSTANDING, v.117, no.6, pp.660 - 669
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.
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DOI
10.1016/j.cviu.2013.02.003
ISSN
1077-3142
Appears in Collections:
EE_Journal Papers
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