The goal of this project was to extract key features from photographs of faces and use machine learning to classify subjects as either sober or drunk. To do this we analyzed photographs of 53 subjects after drinking wine and extracted key features which we used to classify drunkenness. We used random forest machine learning to achieve 81% accuracy. We built an android application that using our classifiers to estimate the subjects drunkenness from a selfie.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Roberts, Paul D
• Banatoski, Ian M
• Willoughby, Colin John

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-042518-140028

Advisor

• Agu, Emmanuel O.

Year

• 2018

Date created

• 2018-04-25

Resource type

• Major Qualifying Project

Major

• Computer Science

Rights statement

• In Copyright