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FACIAL POSITION AND EXPRESSION BASED HUMAN
COMPUTER INTERFACE FOR PERSONS WITH TETRAPLEGIA
ABSTRACT
A human computer interface (namely Facial position and expression Mouse system, FM)
for the persons with tetraplegia based on a monocular infrared depth camera is presented in this
paper. The nose position along with the mouth status (close/open) is detected by the proposed
algorithm to control and navigate the cursor as computer user input. The algorithm is based on an
improved Randomized Decision Tree (RDT) which is capable to detect the facial information
efficiently and accurately. A more comfortable user experience is achieved by mapping the nose
motion to the cursor motion via a nonlinear function. The infrared depth camera enables the
system to be independent of illumination and colour changes both from the background and on
human face, which is a critical advantage over RGB camera based options. Extensive
experimental results show that the proposed system outperforms existing Assistive Technologies
(ATs) in terms of quantitative and qualitative assessments.

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Facial position and expression based human computer interface for persons with tetraplegia

  • 1. FACIAL POSITION AND EXPRESSION BASED HUMAN COMPUTER INTERFACE FOR PERSONS WITH TETRAPLEGIA ABSTRACT A human computer interface (namely Facial position and expression Mouse system, FM) for the persons with tetraplegia based on a monocular infrared depth camera is presented in this paper. The nose position along with the mouth status (close/open) is detected by the proposed algorithm to control and navigate the cursor as computer user input. The algorithm is based on an improved Randomized Decision Tree (RDT) which is capable to detect the facial information efficiently and accurately. A more comfortable user experience is achieved by mapping the nose motion to the cursor motion via a nonlinear function. The infrared depth camera enables the system to be independent of illumination and colour changes both from the background and on human face, which is a critical advantage over RGB camera based options. Extensive experimental results show that the proposed system outperforms existing Assistive Technologies (ATs) in terms of quantitative and qualitative assessments.