Detecting and Tracking Distant Objects at Night Based on Human Visual System

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• 作者：Kaiqi Huang ; Liangsheng Wang ; Tieniu Tan
• 刊名：Lecture Notes in Computer Science
• 出版年：2006
• 出版时间：2006
• 年：2006
• 卷：3852
• 期：1
• 页码：pp.822-831
• 全文大小：309 KB
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

Moving object detection is a challenging task for night security because of bad video quality. In this paper, we propose a robust real time objects detection method for night visual surveillance based on human visual system. By measuring contrast information variation in multiple successive frames, a spatio-temporal contrast change image (CCI) is formed. Then the multi-frame correspondence technology is employed to robustly extract salient motions or moving objects from CCI. Since CCI is a statistical measurement of variation based on human visual system, the proposed method is effective at night and better than traditional detection methods. Experiments on real scene show that the method based on contrast feature is effective for night object detection and tracking, our approach is also robust to camera scale variation as well as low computation cost.