Hyper-rectangle based segmentation and clustering of large video data sets

Cited 4 time in webofscience Cited 0 time in scopus
  • Hit : 461
  • Download : 0
Video information processing has been one of great challenging areas in the database community since it needs huge amount of storage space and processing power. In this paper. we investigate the problem of clustering large video data sets that are collections of video clips as foundational work for the subsequent processing such as video retrieval. A video clip, a sequence of video frames, is represented by a multidimensional data sequence, which is partitioned into video segments considering temporal relationship among frames, and then similar segments of the clip are grouped into Video clusters. We present the effective video segmentation and clustering algorithm which guarantees the clustering quality to such an extent that satisfies predefined conditions., and show its effectiveness via experiments on various video data sets. (C) 2002 Elsevier Science Inc. All rights reserved.
Publisher
ELSEVIER SCIENCE INC
Issue Date
2002-03
Language
English
Article Type
Article
Citation

INFORMATION SCIENCES, v.141, no.1-2, pp.139 - 168

ISSN
0020-0255
URI
http://hdl.handle.net/10203/82780
Appears in Collection
CS-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 4 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0