Neural recognition of human pointing gestures in real images
Neural Processing Letters
Hybrid intelligent systems for network security
Proceedings of the 44th annual Southeast regional conference
Linear-Time Computation of Similarity Measures for Sequential Data
The Journal of Machine Learning Research
SOMM: Self organizing Markov map for gesture recognition
Pattern Recognition Letters
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The area of Human-Machine Interface is growing fast due to its high importance in all technological systems The basic idea behind designing Human-Machine interfaces is to enrich the communication with the technology in a natural and easy way Gesture interfaces are a good example of transparent interfaces Such interfaces must perform the action the user wants, so that the proper gesture recognition is of the highest importance However, most of the systems based on gesture recognition use complex methods requiring high-resource devices In this work we propose to model gestures capturing their temporal properties, significantly reducing the storage requirements, and using self-organizing maps for their classification The main advantage of the approach is its simplicity, which enables the implementation using devices with limited resources, and therefore low cost First testing results demonstrate its high potential.