Abstract Detecting and tracking aviator’s hand in the cockpit is a fundamental task on analyzing and identifying the behavior of aviators. Due to the complicated conditions in the cockpit - such as the lighting varies, the space of Cockpit is narrow, the operation of aviator is sophisticated - tracking the hand in Aircraft Cockpit has more difficulties than tracking the hand in human-machine interaction. We propose a hand tracking method to track the aviator’s hand based on depth images. In our experiment, most of the common flight operations are tested. The average error of hand position tracking is 6.4 mm and the ratio of losing tracking is only 1.4%, which indicate that the proposed algorithm has the ability to tracking the aviator’s hand in the aircraft cockpit accurately.
Aviator Hand Tracking Based on Depth Images
01.01.2017
9 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Region growing , Kalman filter , Depth image , Aircraft cockpit , Hand tracking Simulation and Modeling , System Performance and Evaluation , Computer Science , Data Mining and Knowledge Discovery , Special Purpose and Application-Based Systems , Environmental Geography , Information Storage and Retrieval
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