TY - GEN
T1 - Video query processing in the VDBMS testbed for video database research
AU - Aref, Walid
AU - Hammad, Moustafa
AU - Catlin, Ann Christine
AU - Ilyas, Ihab
AU - Ghanem, Thanaa
AU - Elmagarmid, Ahmed
AU - Marzouk, Mirette
PY - 2003
Y1 - 2003
N2 - The increased use of video data sets for multimedia-based applications has created a demand for strong video database support, including efficient methods for handling the content-based query and retrieval of video data. Video query processing presents significant research challenges, mainly associated with the size, complexity and unstructured nature of video data. A video query processor must support video operations for search by content and streaming, new query types, and the incorporation of video methods and operators in generating, optimizing and executing query plans. In this paper, we address these query processing issues in two contexts, first as applied to the video data type and then as applied to the stream data type. We first present the query processing functionality of the VDBMS video database management system as a framework designed to support the full range of functionality for video as an abstract data type. We describe two query operators for the video data type which implement the rank-join and stop-after algorithms. As videos may be considered streams of consecutive image frames, video query processing can be expressed as continuous queries over video data streams. The stream data type was therefore introduced into the VDBMS system, and system functionality was extended to support general data streams. From this viewpoint, we present an approach for defining and processing streams, including video, through the query execution engine. We describe the implementation of several algorithms for video query processing expressed as continuous queries over video streams, such as fast forward, region-based blurring and left outer join. We include a description of the window-join algorithm as a core operator for continuous query systems, and discuss shared execution as an optimization approach for stream query processing.
AB - The increased use of video data sets for multimedia-based applications has created a demand for strong video database support, including efficient methods for handling the content-based query and retrieval of video data. Video query processing presents significant research challenges, mainly associated with the size, complexity and unstructured nature of video data. A video query processor must support video operations for search by content and streaming, new query types, and the incorporation of video methods and operators in generating, optimizing and executing query plans. In this paper, we address these query processing issues in two contexts, first as applied to the video data type and then as applied to the stream data type. We first present the query processing functionality of the VDBMS video database management system as a framework designed to support the full range of functionality for video as an abstract data type. We describe two query operators for the video data type which implement the rank-join and stop-after algorithms. As videos may be considered streams of consecutive image frames, video query processing can be expressed as continuous queries over video data streams. The stream data type was therefore introduced into the VDBMS system, and system functionality was extended to support general data streams. From this viewpoint, we present an approach for defining and processing streams, including video, through the query execution engine. We describe the implementation of several algorithms for video query processing expressed as continuous queries over video streams, such as fast forward, region-based blurring and left outer join. We include a description of the window-join algorithm as a core operator for continuous query systems, and discuss shared execution as an optimization approach for stream query processing.
KW - Continuous query
KW - Query processing
KW - Rank-join algorithm
KW - Stream processing
KW - Video database
KW - Window-join algorithm
UR - http://www.scopus.com/inward/record.url?scp=12244313247&partnerID=8YFLogxK
U2 - 10.1145/951676.951682
DO - 10.1145/951676.951682
M3 - Conference contribution
AN - SCOPUS:12244313247
SN - 1581137265
SN - 9781581137262
T3 - MMDB 2003: Proceedings of the First ACM International Workshop on Multimedia Databases
SP - 25
EP - 32
BT - MMDB 2003
PB - Association for Computing Machinery (ACM)
T2 - MMDB 2003: Proceedings of the First ACM International Workshop on Multimedia Databases
Y2 - 7 November 2003 through 7 November 2003
ER -