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.
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Bianchi, L., Gatti, R., Lombardi, L., Lombardi, P. (2009). Tracking without Background Model for Time-of-Flight Cameras. In: Wada, T., Huang, F., Lin, S. (eds) Advances in Image and Video Technology. PSIVT 2009. Lecture Notes in Computer Science, vol 5414. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92957-4_63
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DOI: https://doi.org/10.1007/978-3-540-92957-4_63
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