TY - GEN
T1 - Fast and robust video clip search using index structure
AU - Duan, Ling Yu
AU - Yuan, Jun Song
AU - Tian, Qi
AU - Xu, Chang Sheng
PY - 2004
Y1 - 2004
N2 - Content based retrieval of similar multimedia objects (e.g. images, text, and videos) is an important research issue in the field of multimedia database. In this demo, we present a fast and robust video clip searching system. This system consists of two major modules, namely, robust video representation and fast searching. Different from traditional key frame-based histogram methods, we employ the cumulative histogram to represent the ordinal features and color range features for a video segment. This representation provides a spatio-temporal description of the whole segment. Our experiment has shown it is effective for capturing the patterns of short video clips such as commercial, program lead in/out, flying logo in sports video, etc. In order to improve the performance in searching large video database, we introduce the index structure to deal with video search from the viewpoint of query processing (e.g. K-NN query, Range query, etc.) in high-dimensional spaces. Different query processing support different search tasks. In this demo, we employ the mrkd-tree index structure and the proposed video representation to fulfill fast and robust search of short video clips (i.e. news video lead-in/out, replay logo, commercial) in large video collections with the total length of 15 hours.
AB - Content based retrieval of similar multimedia objects (e.g. images, text, and videos) is an important research issue in the field of multimedia database. In this demo, we present a fast and robust video clip searching system. This system consists of two major modules, namely, robust video representation and fast searching. Different from traditional key frame-based histogram methods, we employ the cumulative histogram to represent the ordinal features and color range features for a video segment. This representation provides a spatio-temporal description of the whole segment. Our experiment has shown it is effective for capturing the patterns of short video clips such as commercial, program lead in/out, flying logo in sports video, etc. In order to improve the performance in searching large video database, we introduce the index structure to deal with video search from the viewpoint of query processing (e.g. K-NN query, Range query, etc.) in high-dimensional spaces. Different query processing support different search tasks. In this demo, we employ the mrkd-tree index structure and the proposed video representation to fulfill fast and robust search of short video clips (i.e. news video lead-in/out, replay logo, commercial) in large video collections with the total length of 15 hours.
KW - Index structure
KW - Mrkd-tree
KW - Query processing
KW - Video clip search
UR - https://www.scopus.com/pages/publications/13444287754
U2 - 10.1145/1027527.1027701
DO - 10.1145/1027527.1027701
M3 - Conference contribution
AN - SCOPUS:13444287754
SN - 1581138938
SN - 9781581138931
T3 - ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia
SP - 756
EP - 757
BT - ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia
PB - Association for Computing Machinery
T2 - ACM Multimedia 2004 - proceedings of the 12th ACM International Conference on Multimedia
Y2 - 10 October 2004 through 16 October 2004
ER -