Abstract
Nowadays, hand detection and gestures recognition have become very popular in human computer interaction systems. Several methods of hand detection based on wrist localization have been proposed but the majority work only with short sleeves and they are not efficient in front of all the challenges. Hand detection based on wrist localization proposed by Grzejszczak et al. (Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013 439–449, 2013), Nelpa et al. (Man Mach Interact 3(242):123–130, 2014) [3, 4] use the property of local minima along the contour of the skin mask obtained in the first stage to detect the wrist position. Although this technique provides good results where the skin mask contains the hand and the forearm, it still sensitive to the short contour where the skin mask contains the hand region only which generate false detection of the hand. We present in this paper an assessment of this method where the skin mask contains the hand region only. The main idea is based on the 2D shape properties of the hand and its components. Using 134 color images with their ground- truth, we evaluated the method enhanced and the results obtained were very satisfactory compared to the original one.
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Medjram, S., Babahenini, M.C., Yamina, M.B.A., Taleb-Ahmed, A. (2016). Improving the Method of Wrist Localization Local Minimum-Based for Hand Detection. In: Chikhi, S., Amine, A., Chaoui, A., Kholladi, M., Saidouni, D. (eds) Modelling and Implementation of Complex Systems. Lecture Notes in Networks and Systems, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-33410-3_11
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DOI: https://doi.org/10.1007/978-3-319-33410-3_11
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