Image Segmentation and Range Estimation Using a Moving-aperture Lens

Abstract

Given 2D images, it still remains a big challenge in the field of computer vision to group the image points into logical objects (segmentation) and to determine the locations in the scene (range estimation). Despite the decades of research, a single solution is yet to be found. Through our research we have demonstrated that a possible solution is to use moving aperture lens. This lens has the effect of introducing small, repeating movements of the camera center so that objects appear to translate in the image, by an amount that depends on distance from the plane of focus. Our novel method employs optical flow techniques to an image sequence, captured using a video camera with a moving aperture lens. For a stationary scene, optical flow magnitudes and direction are directly related to the three-dimensional object distance and location from the observer. Exploiting this information, we have successfully extracted objects at different depths and estimated the locations of objects in the scene, with respect to the plane of focus. Our work therefore demonstrates an ability for passive range estimation, without emitting any energy in an environment. Other potential applications include video compression, 3D video broadcast, teleconferencing and autonomous vehicle navigation.