Comments on “Real Time Gesture Learning and Recognition: Towards Automatic Categorization”
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The document provides comments on the paper "Real Time Gesture Learning and Recognition: Towards Automatic Categorization". It summarizes that the paper presents techniques to recognize gestures from accelerometer sensor data using supervised learning for fixed length gestures and unsupervised learning for variable length gestures. Comments praise the clear structure and use of graphs for data visualization, while noting some technical terms may be unfamiliar to broader audiences.
Comments on “Real Time Gesture Learning and Recognition: Towards Automatic Categorization”
- 1. Comments on “Real Time Gesture Learning and Recognition: Towards Automatic Categorization” Muhammad Ikhsan Assaat Scientific Writing Class Baptiste Caramiaux, Patrick Susini, Tommaso Bianco, Frédéric Bevilacqua, Olivier Houix, Norbert Schnell, Nicolas Misdariis, Gestural Embodiment of Environmental Sounds : an Experimental Study, Proceedings of the International Conference on New Interfaces for Musical Expression, pp. 144–148, 2011.
- 2. Structure • Clear Structure • Abstract, Introduction, Methods, Results, Discussions, Conclusion, Future Work
- 3. Clarity • Usage of graphs for data visualization • Technical terms although people in the respected field should be familiar
- 4. Content • Techniques to recognize gestures from accelerometer sensor (Wii controller) • Recognize a fixed length gesture with supervised method • Recognize various length gesture with unsupervised method • Related work around gesture recognition field
- 5. Understanding • Conference tend to have specified format • Structure gives readers familiarity