Do We Need Complex Models for Gestures? A Comparison of Data Representation and Preprocessing Methods for Hand Gesture Recognition

Human-Computer Interaction (HCI) is one of the most rapidly developing fields of computer applications. One of approaches to HCI is based on gestures which are in many cases more natural and effective than conventional inputs. In the paper the problem of gesture recognition is investigated. The gestures are gathered from the dedicated motion capture system, and further evaluated by 3 different preprocessing procedures and 4 different classifier. Our results suggest that most of the combinations produce adequate recognition rate, with appropriate signal normalization being the key element.

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