Improving face detection with depth

Abstract

Face detection serves an important role in many computer vision systems. Typically, a face detector identifies faces within a grayscale or color image. Due to the recent increase in consumer depth cameras, obtaining both color and depth images of a scene has never been easier. We propose a technique that utilizes depth information to improve face detection. Standard face detection methods, such as the Viola-Jones object detection framework, detects faces by searching an image at every location and scale. Our method increases the speed and accuracy of the Viola-Jones face detector by utilizing depth data to constrain the detector's search over the image. Leveraging a Kinect camera, we are able to detect faces 3.5× faster, while greatly reducing the amount of false positives.