Data-driven approach to human motion modeling with Lua and gesture description language

Tomasz Hachaj; Katarzyna Koptyra; Marek R. Ogiela

doi:10.1117/12.2268653

17 March 2017 Data-driven approach to human motion modeling with Lua and gesture description language

Tomasz Hachaj, Katarzyna Koptyra, Marek R. Ogiela

Proceedings Volume 10341, Ninth International Conference on Machine Vision (ICMV 2016); 1034109 (2017) https://doi.org/10.1117/12.2268653
Event: Ninth International Conference on Machine Vision, 2016, Nice, France

Abstract

The aim of this paper is to present the novel proposition of the human motion modelling and recognition approach that enables real time MoCap signal evaluation. By motions (actions) recognition we mean classification. The role of this approach is to propose the syntactic description procedure that can be easily understood, learnt and used in various motion modelling and recognition tasks in all MoCap systems no matter if they are vision or wearable sensor based. To do so we have prepared extension of Gesture Description Language (GDL) methodology that enables movements description and real-time recognition so that it can use not only positional coordinates of body joints but virtually any type of discreetly measured output MoCap signals like accelerometer, magnetometer or gyroscope. We have also prepared and evaluated the cross-platform implementation of this approach using Lua scripting language and JAVA technology. This implementation is called Data Driven GDL (DD-GDL). In tested scenarios the average execution speed is above 100 frames per second which is an acquisition time of many popular MoCap solutions.

Citation Download Citation

Tomasz Hachaj, Katarzyna Koptyra, and Marek R. Ogiela "Data-driven approach to human motion modeling with Lua and gesture description language", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 1034109 (17 March 2017); https://doi.org/10.1117/12.2268653

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