Depth gradient based segmentation of overlapping foreground objects in range images
Andre Stormer, Martin O. Hofmann, Gerhard Rigoll · 2010
Using standard background modeling approaches, close or overlapping objects are often detected as a single blob. In this paper we propose a new and effective method to distinguish between overlapping foreground objects in data obtained from a time of flight sensor. For this we use fusion of the infrared and the range data channels. In addition a further processing step is introduced to evaluate if connected components should be further divided. This is done using nonmaximum suppression on strong depth gradients.