Authors:
Paulo Trigueiros
1
;
Fernando Ribeiro
2
and
Luis Paulo Reis
3
Affiliations:
1
University of Minho, Portugal
;
2
Universidade do Minho, Portugal
;
3
University of Minho / LIACC, Portugal
Keyword(s):
Hand Gesture Recognition, Machine Vision, Hand Features, Hog, Fourier Descriptors, Centroid Distance, Radial Signature, Shi-Tomasi Corner Detection.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Data Manipulation
;
Enterprise Information Systems
;
Evolutionary Computing
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Intelligent User Interfaces
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Machine Learning
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
;
Symbolic Systems
;
Vision and Perception
Abstract:
Vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition. 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. In this paper we present a comparative study of seven different algorithms for hand feature extraction, for static hand gesture classification, analysed with RapidMiner in order to find the best learner. We defined our own gesture vocabulary, with 10 gestures, and we have recorded videos from 20 persons performing the gestures for later processing. Our goal in the present study is to learn features that, isolated, respond better in various situations in human-computer interaction. Results show that the radial signature and the centroid distance are the features that when used sep
arately obtain better results, being at the same time simple in terms of computational complexity.
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