Affiliations: [a] Facultad de Ciencias de la Computación, Benemérita Universidad Autónoma de Puebla, Mexico
| [b] Université catholique de Louvain (UCLouvain), LouRIM. Place des Doyens, 1. B-1348 Louvain-la-Neuve, Belgium
Correspondence:
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Corresponding author. David Céspedes-Hernández, Facultad de Ciencias de la Computación, Benemérita Universidad Autónoma de Puebla, Mexico. Tel. +52 12 345 678; Fax. +52 13 678 789; E-mail: dcespedesh@gmail.com.
Abstract: A gesture elicitation study consists of a popular method for eliciting a sample of end end users to propose gestures for executing functions in a certain context of use, specified by its users and their functions, the device or the platform used, and the physical environment in which they are working. Gestures proposed in such a study needs to be classified and, perhaps, extended in order to feed a gesture recognizer. To support this process, we conducted a full-body gesture elicitation study for executing functions in a smart home environment by domestic end users in front of a camera. Instead of defining functions opportunistically, we define them based on a taxonomy of abstract tasks. From these elicited gestures, a XML-compliant grammar for specifying resulting gestures is defined, created, and implemented to graphically represent, label, characterize, and formally present such full-body gestures. The formal notation for specifying such gestures is also useful to generate variations of elicited gestures to be applied on-the-fly on gestures in order to allow one-shot learning.
