The Ability Test of Model the Facial Landmark Detecting
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Abstract
Recently, there are several techniques for face detection such as detecting the whole face or detecting specific parts of face by using artificial intelligence. For this project, facial landmarks model was conducted to detect 68 points of different face parts. Each facial point could be calculated to generate values. Moreover, various face motion photos were applied into 1,522 datasets to examine the accuracy of the facial landmarks model. The result showed that the accuracy of using model was very high which was 94.81%. Besides, the model was conducted to detect unusual long closed-eyes and opened-mouth by comparing 2 tools between Nvidia Jetson Nano and Raspberry Pi 4 + Intel® Neural Compute Stick 2 with webcam camera. There were 4 circumstances to test the detection of facial points and the average accuracy of each tool was 78.08% and 80.59% respectively.
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