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NATURAL INTERACTION PROTOTYPES BY MEANS OF ENACTIVE
INTERFACES BASED ON VISUAL INPUTS

Research – Gesture recognition

In most of the existing human–computer interfaces, enactive knowledge as new natural interaction paradigm has not been fully exploited yet. Recent technological advances have created the possibility to enhance naturally and significantly the interface perception by means of visual inputs, the so-called Vision-Based Interfaces (VBI). In the present paper, we explore the
recovery of the user’s body posture by means of combining robust computer vision techniques and a well known inverse kinematics algorithm in realtime.

Specifically, we focus on recognizing the user’s motions with a particular mean, that is, a body gesture. Defining an appropriate representation of the user’s body posture based on a temporal
parameterization, we apply non-parametric techniques to learn and recognize the user’s body gestures. This scheme of recognition has been applied to control a compute

postura0

 

 

gestos

References
Boulic, R.; Varona, J.; Unzueta, L.; Peinado, M.; Suescun, A.; Perales, F.J.,
“Evaluation of on-line analytic and numeric inverse kinematics approaches driven
by partial vision input”. Virtual Reality 10(1): 48-61, 2006.

A case study: videogame control through body gestures