.png){kind=icon}
.png){kind=icon}
Return
Automatic objects behaviour recognition from compressed video domain
.png){kind=icon}
PRE
AI
DOI：10.1016/j.imavis.2008.07.002.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper we present a system that, directly from compressed video domain, establishes a correspondence between objects in motion in a video scene and a concrete behaviour. This behaviour is expressed by using linguistic variables. Besides, with this fuzzy logic-based approach, the imprecision and vagueness of our primary source of information, MPEG motion vectors, is reduced. Proposed algorithms for segmentation and tracking are based on fuzzification of MPEG motion data. Once the tracking phase has finished, a linguistic model for each objective in the scene is generated and compared with each one of the behaviour models previously described in a linguistic manner. Finally, a practical application of this system for detection, tracking and behaviour analysis of vehicles in complex traffic scenes is presented. (C) 2008 Elsevier B.V. All rights reserved.
Keywords:
Fuzzy logic
Linguistic labels
MPEG compressed video
Behaviour models
Vehicles tracking
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.2
Papers:
4.0K
Citations:
6.7K