Alessandro Carcangiu
Lucio Davide Spano
ABSTRACT
In the last years, the introduction of new, precise and pervasive tracking devices has contributed to the popularity of gestural interaction. In general, the effectiveness of such interfaces depends on two components: the algorithm used for accurately recognizing the user movements and the guidance provided to users while executing gestures. In this paper, we discuss a work in progress research for connecting these two components and increasing their effectiveness: the recognition algorithm supports the implementation of feedback the and feed-forward mechanisms, providing information on the identified gesture parts in real time, while developers define complex gestures starting from simple primitives.
- Alessandro Carcangiu, Lucio Davide Spano, Giorgio Fumera, and Fabio Roli. 2017. Gesture modelling and recognition by integrating declarative models and pattern recognition algorithms. In International Conference on Image Analysis and Processing. Springer, 84--95.Google Scholar
Cross Ref
- Alessandro Carcangiu, Lucio Davide Spano, Giorgio Fumera, and Fabio Roli. 2019. DEICTIC: A compositional and declarative gesture description based on hidden markov models. International Journal of Human-Computer Studies 122 (2019), 113--132.Google ScholarCross Ref
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Index Terms
- Integrating declarative models and HMMs for online gesture recognition
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