FEOGARM: A Framework to Evaluate and Optimize Gesture Acquisition and Recognition Methods
Simon Ruffieux, Elena Mugellini, Omar Abou Khaled · 2011
Abstract�This paper discusses the general concept and implementation steps towards a framework facilitating the development and evaluation of gesture acquisition and recognition systems through a common benchmarking standard. In particular, a complete ground-truth of annotated gestures will be acquired with multiple high-resolution acquisition devices and as such will facilitate, using machine-learning techniques, the development of non-intrusive and light capture devices dedicated to gestures recognition. This article presents our concept, the current achievements and the first steps towards such a framework and corpus. Keywords-gesture recognition; open-source corpus; framework; algorithms evaluation and optimization I.