Gesture recognition on smart cameras

Aziz Dziri; Stephane Chevobbe; Mehdi Darouich

doi:10.1117/12.2007583

19 February 2013 Gesture recognition on smart cameras

Aziz Dziri, Stephane Chevobbe, Mehdi Darouich

Proceedings Volume 8659, Sensors, Cameras, and Systems for Industrial and Scientific Applications XIV; 86590L (2013) https://doi.org/10.1117/12.2007583
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

Gesture recognition is a feature in human-machine interaction that allows more natural interaction without the use of complex devices. For this reason, several methods of gesture recognition have been developed in recent years. However, most real time methods are designed to operate on a Personal Computer with high computing resources and memory. In this paper, we analyze relevant methods found in the literature in order to investigate the ability of smart camera to execute gesture recognition algorithms. We elaborate two hand gesture recognition pipelines. The first method is based on invariant moments extraction and the second on finger tips detection. The hand detection method used for both pipeline is based on skin color segmentation. The results obtained show that the un-optimized versions of invariant moments method and finger tips detection method can reach 10 fps on embedded processor and use about 200 kB of memory.

Citation Download Citation

Aziz Dziri, Stephane Chevobbe, and Mehdi Darouich "Gesture recognition on smart cameras", Proc. SPIE 8659, Sensors, Cameras, and Systems for Industrial and Scientific Applications XIV, 86590L (19 February 2013); https://doi.org/10.1117/12.2007583

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KEYWORDS

Gesture recognition

Image processing

Skin

Detection and tracking algorithms

Image resolution

Image segmentation

RGB color model

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