Probabilistic-topological calibration of widely distributed camera networks

Abstract We propose a method for estimating the topology of distributed cameras, which can provide useful information for multi-target tracking in a wide area, without object identification among the FOVs of the cameras. In our method, each camera first detects objects in its observed images independently in order to obtain the positions/times where/when the objects enter/exit its FOV. Each obtained data is tentatively paired with all other data detected before the data is observed. A transit time between each paired data and their x-y coordinates are then computed. Based on classifying the distribution of the transit times and the x-y coordinates, object routes between FOVs can be detected. The classification is achieved by simple and robust vector quantization. The detected routes are then categorized to acquire the probabilistic-topological information of distributed cameras. In addition, offline tracking of observed objects can be realized by means of the calibration process. Ex...

• Type: Journal
• Year: 2007
• Where: MVA
• Authors: Norimichi Ukita
• Keywords: Camera, Computer Vision, MVA 2007, Transit Times, X-y Coordinates