Evaluation of a Foreground Segmentation Algorithm for 3D Camera Sensors

Our interest is focusing on the innovative time-of-flight (TOF) cameras. In this paper we present our approach to foreground segmentation, based on smart-seeded region growing. The seeding strategy makes use of the characteristic intensity signal provided by TOF cameras, and growing is proved by experimental measurements to produce a pixel-wise segmentation of 82%-92% quality. Compared to background subtraction, our approach uses more explicitly the unique capacity of TOF cameras to isolate foreground objects on the basis of their distance. Our work will find an application in gate monitoring and passage surveillance.

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