Abstract
Applications that add filters/effects to one’s face have become extremely popular as of late. Mobile phone users have developed a new demand for applications which can take their selfies to the next level by adding fun effects. The goal of this project was to learn more about the technologies that go into face detection, feature recognition, and image warping in order to help others gain a better understanding of the core concepts behind hugely popular applications like Snapchat. Previous projects demonstrate this same goal although with less accuracy in filter placement and more pixilation and noise around the edges of filters. To enhance filter placement, we utilize OpenCV and DLib for accurate face detection and detailed facial feature point recognition. In addition, we explore a simple method by which to inform the program how a filter should fit onto to a face. We also implement a method of alpha blending for clean compositing of transparent filters over images. We hope this project gives others the confidence to explore this quickly emerging area of computational photography and further improve on our work.
Results
(Left) Original Dwight.
(Below) Filters automatically fitted by our program
Click here for video output
