Principal Axis-Based Correspondence between Multiple Cameras for People Tracking

Visual surveillance using multiple cameras has attracted increasing interest in recent years. Correspondence between multiple cameras is one of the most important and basic problems which visual surveillance using multiple cameras brings. In this paper, we propose a simple and robust method, based on principal axes of people, to match people across multiple cameras. The correspondence likelihood reflecting the similarity of pairs of principal axes of people is constructed according to the relationship between "ground-points" of people detected in each camera view and the intersections of principal axes detected in different camera views and transformed to the same view. Our method has the following desirable properties: 1) Camera calibration is not needed. 2) Accurate motion detection and segmentation are less critical due to the robustness of the principal axis-based feature to noise. 3) Based on the fused data derived from correspondence results, positions of people in each...

• Type: Journal
• Year: 2006
• Where: PAMI
• Authors: Weiming Hu, Min Hu, Xue Zhou, Tieniu Tan, Jianguang Lou, Stephen J. Maybank
• Keywords: Camera, Multiple Cameras, PAMI 2006, Principal Axes