Aviator Hand Tracking Based on Depth Images
Aviator Hand Tracking Based on Depth Images
- New search for: Wang, Xiaolong
- New search for: Fu, Shan
- New search for: Wang, Xiaolong
- New search for: Fu, Shan
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.
Document information
Aviator Hand Tracking Based on Depth Images
2017-01-01
9 pages
Article/Chapter (Book)
Electronic Resource
English
Aircraft cockpit , Hand tracking , Depth image , Kalman filter , Region growing Computer Science , Information Storage and Retrieval , Data Mining and Knowledge Discovery , Special Purpose and Application-Based Systems , System Performance and Evaluation , Simulation and Modeling , Environmental Geography
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