Profile face detection using flipping scheme with genetic algorithm

Mengbo You, Takuya Akashi

Abstract: This paper adopts the genetic algorithm optimized flipping scheme to transform the frontal face detector to be profile face detectors for various profile views, rather than the normally building different detectors for different views, or small view ranges. The flipping scheme takes advantage of the over-representation characteristic of the frontal face detector trained with the SURF cascade framework. However, the previous flipping scheme utilizes the classic sliding window method to search for the the hypothetical face axis of symmetry, which is time-consuming. This paper treats this searching as an optimization problem and use the genetic algorithm to optimize the coordinates, the scale and rotation angle of the profile face. We implemented the real time detection of profile faces from different views with genetic algorithm optimized flipping scheme.