Time-of-Flight cameras are the state of art sensors for a fast detection of depth data in a scene. This kind of sensors can be very useful for tracking, in particular in indoor ambient, since, using light in near-infrared spectrum, they are less affected by abrupt change in illumination. In this paper we propose a new method for the tracking of multiple subjects based on Kalman filter. The first step of our solution is a ToF based foreground segmentation, that retrieves all significant clusters in the scene, followed by a robust tracking system able to correctly handle occlusions and possible merging between clusters. © 2013 Springer-Verlag.
CITATION STYLE
Dondi, P., Lombardi, L., & Cinque, L. (2013). Multisubjects tracking by time-of-flight camera. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8156 LNCS, pp. 692–701). https://doi.org/10.1007/978-3-642-41181-6_70
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