Abstract
In modern society there is an increasing demand to access, record and manipulate large amounts of information. This has inspired a new approach to thinking about and designing personal computers, where the ultimate goal is to produce a truly wearable computer. In this work we present a non-invasive hand-gesture recognition system aimed at deictic gestures. Our system is based on the powerful Sequential Monte Carlo framework which is enhanced with respect to increased robustness. This is achieved by using ratios in the likelihood function together with two image cues: edges and skin color. The system proves to be fast, robust towards noise, and quick to lock on to the object (hand). All of which is achieved without the use of special lighting or special markers on the hands, hence our system is a non-invasive solution.
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Moeslund, T.B., Nørgaard, L. (2006). Recognition of Deictic Gestures for Wearable Computing. In: Gibet, S., Courty, N., Kamp, JF. (eds) Gesture in Human-Computer Interaction and Simulation. GW 2005. Lecture Notes in Computer Science(), vol 3881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11678816_13
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DOI: https://doi.org/10.1007/11678816_13
Publisher Name: Springer, Berlin, Heidelberg
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