24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Türkiye, 16 - 19 Mayıs 2016, ss.1477-1480
With the development of consumer depth sensors, research on human detection and tracking from depth images has gained momentum. Depth information facilitates the extraction of objects from the background, and enables localization of these objects in 3D space. In this work, we present a new dataset of depth images acquired from indoor environments, such as home, office, coffee shop, where people are present in a variety of poses. We propose a new method for detection of unmoving humans, and test our algorithm on our new dataset.