Abstract
Smile is one of the important emotions that is essential in computer vision tasks. The greatly influenced part due to it is the lips. By encountering the changes in lips of smile images with respect to no smile, a smile detecting model can design for the computer vision tasks. In this paper, the approach is to evaluate the spread of lips. The lips movement distance is evaluated with respect to the eyes. 68 landmark points of dlib are used for this purpose. The left and right corners of lips are evaluated with the left and right eyes respectively using the count of landmark points (l and r). The secondary parameters - average, Maximum, and maxavgsum of l and r are used for evaluating the lip expansion variation. For each value of these parameters that can attain from l and r, the count of no smile images below it and count of smile images above it is considered and calculated the attainable efficiency. The value of secondary parameter having the maximum efficiency is defined as the threshold. The maximum efficiency that is attained due to average, Maximum and maxavgsum are 80.06, 67.3 and 78.54 respectively at the thresholds 2, 3 and 4.5 respectively.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
