In this paper novel 2D-hand tracking algorithms used in a system for hand gesture interaction are presented. New types of head-mounted Augmented-Reality devices offer the possibility to visualize digital content in the user's field of view. To interact with these head-mounted devices hand gestures are an intuitive modality. Generally, the recognition of hand gestures consists of two main steps: The first one is hand tracking and the second step gesture recognition. This paper concentrates on the first step: Hand tracking. Due to the wearing comfort of the glasses-like systems these only use a single camera to capture the field of view of the user. Therefore new algorithms for hand tracking without depth data are presented and compared to state-of-the-art algorithms by utilizing a thorough evaluation methodology for comparing trajectories. © 2013 Springer-Verlag.
CITATION STYLE
Hammer, J. H., & Beyerer, J. (2013). Robust hand tracking in realtime using a single head-mounted RGB camera. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8007 LNCS, pp. 252–261). https://doi.org/10.1007/978-3-642-39330-3_27
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