Pose robust human detection using multiple oriented 2d elliptical filters
VNBA '08 Proceedings of the 1st ACM workshop on Vision networks for behavior analysis
Real-time video surveillance based on combining foreground extraction and human detection
MMM'08 Proceedings of the 14th international conference on Advances in multimedia modeling
Automatic scene calibration for detecting and tracking people using a single camera
Engineering Applications of Artificial Intelligence
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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.