Indoor head detection and tracking on RGBD images
Katarzyna Niżałowska, Łukasz Burdka, Urszula Markowska-Kaczmar
Citation: Proceedings of the 2014 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 2, pages 679–686 (2014)
Abstract. A real-time human head detection and tracking method for a fall detection system is presented. It utilizes RGBD images to obtain a head position in the three-dimensional space. The proposed method is designed to be insensitive to a body orientation and requires no initial calibration for the tracked person. The evaluation was performed on the basis of annotated videos with realistic non-studio indoor everyday activities and falls. The proposed method outperforms head tracking from the Microsoft Kinect SDK skeleton tracking.