Compressed domain video retrieval using object and global motion descriptors

Authors:
R. Venkatesh Babu;K. R. Ramakrishnan
Affiliations:
Department of Electrical Engineering, Indian Institute of Science, Bangalore, India 560 012;Department of Electrical Engineering, Indian Institute of Science, Bangalore, India 560 012
Venue:
Multimedia Tools and Applications
Year:
2007

Citing 0
Cited 4

Video Retrieval Method Using Non-parametric Based Motion Classification

ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Compressed domain indexing of scalable H.264/SVC streams

Image Communication
Motion region-based trajectory analysis and re-ranking for video retrieval

ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
A comprehensive review of significant researches on content based indexing and retrieval of visual information

Frontiers of Computer Science: Selected Publications from Chinese Universities

Quantified Score

Hi-index	0.00

Visualization

Abstract

Video content description has become an important task with the standardization effort of MPEG-7, which aims at easy and efficient access to visual information. In this paper we propose a system to extract object-based and global features from compressed MPEG video using the motion vector information for video retrieval. The reliability of the motion information is enhanced by a motion accumulation process. The global features like motion activity and camera motion parameters are extracted from the above enhanced motion information. The object features such as speed, area and trajectory are then obtained after the proposed object segmentation. The number of objects in a given video shot is determined by the proposed K-means clustering procedure. The object segmentation is done by applying EM algorithm.