Generic System for Human-Computer Gesture Interaction

• Type: Article in International Conference Proceedings Book
• Date: 2014

Authors

trigueiros, p (Author) Other; ribeiro, fr (Author) Other; reis, lp (Author) FCUP

Conference proceedings International

Title: 2014 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2014

Pages: 175-180

IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

Espinho, PORTUGAL, MAY 14-15, 2014

Indexing

ISI Web of Knowledge - 4 Citations

Scopus - 10 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-009-PZX

DOI: 10.1109/ICARSC.2014.6849782

Abstract (EN): Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6