Authors:
Damiano Malafronte
and
Nicoletta Noceti
Affiliation:
Università degli Studi di Genova, Italy
Keyword(s):
Natural User Interfaces, Gesture Recognition, Hand Pose Classification, Fingers Detection.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Enterprise Information Systems
;
Human and Computer Interaction
;
Human-Computer Interaction
;
Image and Video Analysis
;
Shape Representation and Matching
Abstract:
In this paper we consider the problem of recognizing dynamic human gestures in the context of human-machine interaction. We are particularly interested to the so-called Natural User Interfaces, a new modality based on a more natural and intuitive way of interacting with a digital device. In our work, a user can interact with a system by performing a set of encoded hand gestures in front of a webcam. We designed a method that first classifies hand poses guided by a finger detection procedure, and then recognizes known gestures with a syntactic approach. To this purpose, we collected a sequence of hand poses over time, to build a linguistic gesture description. The known gestures are formalized using a generative grammar. Then, at runtime, a parser allows us to perform gesture recognition leveraging on the production rules of the grammar. As for finger detection, we propose a new method which starts from a distance transform of the hand region and iteratively scans such region accordin
g to the distance values moving from a fingertip to the hand palm. We experimentally validated our approach, showing both the hand pose classification and gesture recognition
performances.
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