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In this paper, a real time dynamic gesture recognition method based on a modified Levenshtein distance is proposed. The method addresses the issues faced in dynamic gesture recognition methods that are due to gesture variability within the class due to differences in the gesture speed. Since the gesture speed and duration will vary from one gesture to another, or from one person to the next, without...
In this paper, we propose an efficient real time tracker that uses a differential evolution strategy within the particle filter framework. Particles are strategically propagated based on the maximum a posterior (most likely) object location with genetic operators. This enables the use of a small sample size and alleviates the frequent sample degeneracy and impoverishment problems encountered in particle...
The core element of a dynamic gesture recognition system is to localize the gesturing object, then some classification methods are used to recognize gestures. In this work, focus is made on gesturing object localization. Adaptive differential evolution algorithm for real-time object tracking is proposed. The algorithm tracks the hand position in any directions at variable speed of gesturing, providing...
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