Vector quantization and signal compression
Vector quantization and signal compression
Video parsing and browsing using compressed data
Multimedia Tools and Applications
Digital Video: An introduction to MPEG-2
Digital Video: An introduction to MPEG-2
NeTra: a toolbox for navigating large image databases
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
Content-Based Representative Frame Extraction for Digital Video
ICMCS '98 Proceedings of the IEEE International Conference on Multimedia Computing and Systems
A fully automated content-based video search engine supporting spatiotemporal queries
IEEE Transactions on Circuits and Systems for Video Technology
NeTra-V: toward an object-based video representation
IEEE Transactions on Circuits and Systems for Video Technology
Proceedings of the tenth ACM international conference on Multimedia
Automatic summarization of music videos
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Proceedings of the ACM International Conference on Image and Video Retrieval
Fast video retrieval via the statistics of motion within the regions-of-interest
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
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A novel motion activity descriptor and its extraction from a compressed MPEG (MPEG-1/2) video stream are presented. The descriptor consists of two parts, a temporal descriptor and a spatial descriptor. To get the temporal descriptor, the "motion intensity" is first computed based on P frame macroblock information. Then the motion intensity histogram is generated for a given video unit as the temporal descriptor. To get the spatial descriptor, the average magnitude of the motion vector in a P frame is used to threshold the macro-blocks into "zero" and "non-zero" types. The average magnitude of the motion vectors and three types of runs of zeros in the frame are then taken as the spatial descriptor. Experimental results show that the proposed descriptor is fast, and that the combination of the temporal and spatial attributes is effective. Key elements of the intensity parameter, spatial parameters and the temporal histogram of the descriptor have been adopted by the draft MPEG-7 standard [10].