JOURNAL ARTICLE

Content-based video retrieval using motion descriptors extracted from compressed domain

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 the features from compressed MPEG video based on the motion vector information. The global features like motion activity and camera motion parameters are extracted from the decoded motion vectors and the object features such as speed, area and trajectory are obtained after the object segmentation stage. The number of objects in a given video shot is determined by the proposed K-means clustering algorithm and the object segmentation is done by applying EM algorithm.

Keywords:
Computer science Artificial intelligence Computer vision Motion vector Block-matching algorithm Motion compensation Segmentation Cluster analysis Quarter-pixel motion Video tracking Motion (physics) Trajectory Motion estimation Object (grammar) Image segmentation Pattern recognition (psychology) Image (mathematics)

Metrics

12
Cited By
0.52
FWCI (Field Weighted Citation Impact)
8
Refs
0.69
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Video Analysis and Summarization
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
© 2026 ScienceGate Book Chapters — All rights reserved.