Towards Perceptual Interface for Visualization Navigation of Large Data Sets

Abstract

This paper presents a perceptual interface for visualization navigation using gesture recognition. Scientists are interested in developing interactive settings for exploring large data sets in an intuitive environment. The input consists of registered 3-D data. Bezier curves are used for trajectory analysis and classification of gestures. The method is robust and reliable: correct hand identification rate is 99.9% (from 1641 frames), modes of hand movements are correct 95.6% of the time, recognition rate (given the right mode) is 97.9%. An application to gesture-controlled visualization is also presented. The paper advances the state-of-the-art of human-computer interaction with a robust attachment- and marker-free gestural information processing for visualization.