Title
Surveillance video synopsis in the compressed domain for fast video browsing
Abstract
The traditional pixel-domain based video analysis methods have taken dominated places for long. However, due to the rapidly increasing volume and resolution of surveillance video, the desirable fast and scalable browsing encounters significant challenges in terms of efficiency and flexibility. Under this circumstance, operating surveillance video in compressed domain has aroused great concern in academy and industry. In order to perform the intelligent video analysis task on the premise of preserving accuracy and controlling complexity, this paper presents a compressed-domain approach for massive surveillance video synopsis generation, labeling and browsing. The main work and achievements include: (1) a compressed-domain scheme is established to condense the compressed surveillance video and record the synopsis results; (2) a background modeling method via the Motion Vector based Local Binary Pattern (MVLBP) is introduced to extract moving objects in an efficient way; (3) an object flags based synopsis labeling method is proposed to represent the object regions as well as their display modes in a flexible way. Experimental results show that the video analysis system based on this framework can provide not only efficient synopsis generation but also flexible scalable or playback browsing.
Year
DOI
Venue
2013
10.1016/j.jvcir.2013.10.001
J. Visual Communication and Image Representation
Keywords
Field
DocType
surveillance video synopsis,synopsis result,scalable browsing,efficient synopsis generation,background modeling method,video analysis system,video analysis method,intelligent video analysis task,massive surveillance video synopsis,fast video browsing,surveillance video,playback browsing
Video browsing,Computer vision,Video processing,Computer science,Multiview Video Coding,Video tracking,Smacker video,Artificial intelligence,Video compression picture types,Uncompressed video,Motion vector
Journal
Volume
Issue
ISSN
24
8
1047-3203
Citations 
PageRank 
References 
7
0.50
36
Authors
3
Name
Order
Citations
PageRank
Shi-Zheng Wang1778.39
Hongqiang Wang231340.65
Ruimin Hu3961117.18