Using the Face Tracking Technology to Detect Head Action

• Main Authors: Chen-Yu Ko, 柯政宇
• Other Authors: Jui-Fa Chen
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/42696591685051689603

碩士 === 淡江大學 === 資訊工程學系碩士班 === 101 === Current computer input device’s control method is mostly done by hand operations, but this mode of operation for people with disabilities, especially physical disabilities is quite inconvenient. There are two common computer accessibility for people with disabilities: eye-tracking and head tracking. Eye tracking express less action, and head tracking has three implement method: ultrasound, infrared and face tracking. The implementation use ultrasound or infrared both need to wear equipment, but face tracking is not required, to use for people with disabilities, it is more comfortable. In this thesis, we use Active Shape Model (ASM) to track user’s face feature point, and calculate the translate data and rotation data of the Head, then we use Exponentially-Weighted Moving Average (EWMA) filter to smooth the ''jittery'' raw-data which produce by user because of unconsciously head shaking, then use Levenshtein Distance algorithm and translation data to detect which defined action that user did, at last we match the head action data to the corresponding operation, providing people with disabilities a simple method to control computer.