A comparison of machine learning algorithms applied to hand gesture recognition

• Type: Article in International Conference Proceedings Book
• Date: 2012

Authors

Trigueiros, P (Author) Other; Ribeiro, F (Author) Other; reis, lp (Author) FEUP

Conference proceedings International

Title: INFORMATION SYSTEMS AND TECHNOLOGIES

7th Iberian Conference on Information Systems and Technologies (CISTI)

Madrid, SPAIN, JUN 20-23, 2012

Indexing

ISI Web of Knowledge - 7 Citations

Scopus - 40 Citations

Other information

Authenticus ID: P-002-FVA

Abstract (EN): Hand gesture recognition for human computer interaction is an area of active research in computer vision and machine learning. The primary goal of gesture recognition research is to create a system, which can identify specific human gestures and use them to convey information or for device control. This paper presents a comparative study of four classification algorithms for static hand gesture classification using two different hand features data sets. The approach used consists in identifying hand pixels in each frame, extract features and use those features to recognize a specific hand pose. The results obtained proved that the ANN had a very good performance and that the feature selection and data preparation is an important phase in the all process, when using low-resolution images like the ones obtained with the camera in the current work.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6