Hand Pose Reconstruction Based on Fast Multi-Touch Sensors

Serving as the most widely-used body part for communication, hand is a very important tool for human to interact with the world. Especially with the continuing development of virtual reality and augmented reality, hand pose information has gradually become an indispensable component for improving users’ experience in interacting with computing devices. Therefore, this project aims at achieving hand pose reconstruction based on capacitive sensing technology using machine learning algorithm. The capacitive sensor that will be utilized in this project is supported by the project partner, Tactual Labs who, by the end of this project, will benefit by having its current innovative capacitive controller more intelligent.

Faculty Supervisor:

Karan Singh


Yanjun Jiang


Tactual Labs Co.


Computer science


Information and communications technologies




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