Motion-information-based video retrieval system using rough pre-classification

Authors:
Zhe Yuan;Yu Wu;Guoyin Wang;Jianbo Li
Affiliations:
Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China;Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China;Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China;Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China
Venue:
Transactions on Rough Sets V
Year:
2006

Citing 12
Cited 3

Automatic partitioning of full-motion video

Multimedia Systems
Digital video processing

Digital video processing
Rough sets

Communications of the ACM
A new fast local motion estimation algorithm using global motion

Signal Processing
A Comparison of Several Approaches to Missing Attribute Values in Data Mining

RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
Theoretical Study on Attribute Reduction of Rough Set Theory: Comparison of Algebra and Information Views

ICCI '04 Proceedings of the Third IEEE International Conference on Cognitive Informatics
Motion pattern-based video classification and retrieval

EURASIP Journal on Applied Signal Processing
Determining Three-Dimensional Motion and Structure from Optical Flow Generated by Several Moving Objects

IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of global motion parameters by complex linear regression

IEEE Transactions on Image Processing
Efficient, robust, and fast global motion estimation for video coding

IEEE Transactions on Image Processing
Rapid estimation of camera motion from compressed video with application to video annotation

IEEE Transactions on Circuits and Systems for Video Technology
Support vector machines for histogram-based image classification

IEEE Transactions on Neural Networks

Knowledge Reduction of Covering Approximation Space

Transactions on Computational Science V
Rough sets and near sets in medical imaging: a review

IEEE Transactions on Information Technology in Biomedicine - Special section on body sensor networks
Research on rough set theory and applications in China

Transactions on rough sets VIII

Quantified Score

Hi-index	0.00

Visualization

Abstract

Motion information is the basic element for analyzing video. It represents the change of video on the time-axis and plays an important role in describing the video content. In this paper, a robust motion-based, video retrieval system is proposed. At first, shot boundary detection is achieved by analyzing luminance information, and motion information of video is abstracted and analyzed. Then rough set theory is introduced to classify the shots into two classes, global motions and local motions. Finally, shots of these two types are respectively retrieved according to the motion types of submitted shots. Experiments show that it’s effective to distinguish shots with global motions from those with local motions in various types of video, and in this situation motion-information-based video retrieval are more accurate.