Avaliação das técnicas de segmentação, modelagem e classificação para o reconhecimento automático de gestos e proposta de uma solução para classificar gestos da libras em tempo real

Abstract

Multimodal interfaces are becoming popular and trying to enhance user experience through the use of natural forms of interaction. Among these forms we have speech and gestures inputs. Speech recognition is already a common feature in our daily basis but gesture recognition has just now being widely used as a new form of interaction. The Brazilian Sign Language (Libras) was recently recognized as a legal way of communication since the Brazilian Government enacted the law N˚10.436 on 04/24/2002, and also has recently became an obligatory subject in teachers education and an elective subject in undergraduate courses through the enactment N˚5.626 on 12/22/2005. In this context, this dissertation presents a study of all the steps that are necessary to achieve a complete system to recognize Static and Dynamic gestures of Libras, being these steps: Segmentation; Modeling and Interpretation; and Classification. Results and proposed solutions will be presented for each one of these steps, and the system will be evaluated in the task of real-time recognition of static and dyamic gestures within a finite set of Libras gestures. All the solutions presented in this dissertation were embedded in the software GestureUI, in which the main goal is to simplify the research in the field of gesture recognition allowing the communication with multimodal interfaces through a TCP/IP protocol.