Real-Time Human Detection, Tracking, and Verification in Uncontrolled Camera Motion Environments

In environments where a camera is installed on a freely moving platform, e.g. a vehicle or a robot, object detection and tracking becomes much more difficult. In this paper, we presents a real time system for human detection, tracking, and verification in such challenging environments. To deliver a robust performance, the system integrates several computer vision algorithms to perform its function: a human detection algorithm, an object tracking algorithm, and a motion analysis algorithm. To utilize the available computing resources to the maximum possible extent, each of the system components is designed to work in a separate thread that communicates with the other threads through shared data structures. The focus of this paper is more on the implementation issues than on the algorithmic issues of the system. Object oriented design was adopted to abstract algorithmic details away from the system structure.

[1]  Robert C. Bolles,et al.  Parametric Correspondence and Chamfer Matching: Two New Techniques for Image Matching , 1977, IJCAI.

[2]  Tieniu Tan,et al.  Recent developments in human motion analysis , 2003, Pattern Recognit..

[3]  Yingli Tian S3-R1: the IBM smart surveillance system release 1 , 2005, 14th Annual International Conference on Wireless and Optical Communications, 2005. WOCC 2005.

[4]  A. Hampapur,et al.  Smart video surveillance: exploring the concept of multiscale spatiotemporal tracking , 2005, IEEE Signal Processing Magazine.

[5]  Tieniu Tan,et al.  A survey on visual surveillance of object motion and behaviors , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[6]  Larry S. Davis,et al.  Pedestrian Detection via Periodic Motion Analysis , 2007, International Journal of Computer Vision.

[7]  Sharath Pankanti,et al.  Smart Video Surveillance , 2005 .

[8]  Bernt Schiele,et al.  Towards robust multi-cue integration for visual tracking , 2001, Machine Vision and Applications.

[9]  Thomas B. Moeslund,et al.  A Survey of Computer Vision-Based Human Motion Capture , 2001, Comput. Vis. Image Underst..

[10]  Bernt Schiele,et al.  Towards Robust Multi-cue Integration for Visual Tracking , 2001, ICVS.

[11]  E. Stewart,et al.  Intel Integrated Performance Primitives: How to Optimize Software Applications Using Intel IPP , 2004 .

[12]  Larry S. Davis,et al.  W4: Real-Time Surveillance of People and Their Activities , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Dariu Gavrila,et al.  Pedestrian Detection from a Moving Vehicle , 2000, ECCV.

[14]  George Wolberg,et al.  Robust image registration using log-polar transform , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[15]  Vassilios Morellas,et al.  DETER: Detection of events for threat evaluation and recognition , 2003, Machine Vision and Applications.

[16]  Rama Chellappa,et al.  Visual tracking and recognition using appearance-adaptive models in particle filters , 2004, IEEE Transactions on Image Processing.