Tracking without Background Model for Time-of-Flight Cameras

Authors:
Luca Bianchi;Riccardo Gatti;Luca Lombardi;Paolo Lombardi
Affiliations:
Dept. of Computer Engineering and Systems Science, University of Pavia, Pavia, Italy 27100;Dept. of Computer Engineering and Systems Science, University of Pavia, Pavia, Italy 27100;Dept. of Computer Engineering and Systems Science, University of Pavia, Pavia, Italy 27100;Dept. of Computer Engineering and Systems Science, University of Pavia, Pavia, Italy 27100
Venue:
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Year:
2009

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Abstract

Time-of-flight (TOF) cameras are relatively new sensors that provide a 3D measurement of a scene. By means of the distance signal, objects can be separated from the background on the basis of their distance from the sensor. For virtual studios applications, this feature can represent a revolution as virtual videos can be produced without a studio. When TOF cameras become available to the consumer market, everybody may come to be a virtual studio director. We study real-time fast algorithms to enable unprofessional virtual studio applications by TOF cameras. In this paper we present our approach to foreground segmentation, based on smart-seeded region growing and Kalman tracking. With respect to other published work, this method allows for working with a non-stationary camera and with multiple actors or moving objects in the foreground providing high accuracy for real-time computation.