Cognitive visual tracking and camera control

被引：21

作者：

Bellotto, Nicola ^{[1
]}

Benfold, Ben ^{[2
]}

Harland, Hanno ^{[3
]}

Nagel, Hans-Hellmut ^{[3
]}

Pirlo, Nicola ^{[3
]}

Reid, Ian ^{[2
]}

Sommerlade, Eric ^{[2
]}

Zhao, Chuan ^{[2
]}

机构：

[1] Lincoln Univ, Sch Comp Sci, Lincoln, England

[2] Univ Oxford, Dept Engn Sci, Oxford OX1 2JD, England

[3] Karlsruhe Inst Technol, Inst Algorithmen & Kognit Syst, Karlsruhe, Germany

来源：

COMPUTER VISION AND IMAGE UNDERSTANDING | 2012年 / 116卷 / 03期

关键词：

Cognitive vision; Human tracking; Active cameras; VIDEO; RECOGNITION; BEHAVIOR;

D O I：

10.1016/j.cviu.2011.09.011

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Cognitive visual tracking is the process of observing and understanding the behavior of a moving person. This paper presents an efficient solution to extract, in real-time, high-level information from an observed scene, and generate the most appropriate commands for a set of pan-tilt-zoom (PTZ) cameras in a surveillance scenario. Such a high-level feedback control loop, which is the main novelty of our work, will serve to reduce uncertainties in the observed scene and to maximize the amount of information extracted from it. It is implemented with a distributed camera system using SQL tables as virtual communication channels, and Situation Graph Trees for knowledge representation, inference and high-level camera control. A set of experiments in a surveillance scenario show the effectiveness of our approach and its potential for real applications of cognitive vision, (C) 2011 Elsevier Inc. All rights reserved.

引用

页码：457 / 471

页数：15

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