3D structure estimation from monocular video clips

This paper explores the idea of extracting three dimensional features from a previously recorded video, in an attempt to provide three dimensional information about a video clip in order to improve the performance of various video analysis tasks. Although video analysis is a very prevalent area of research, the use of 3D features is scarce in the literature due to the inherent difficulties associated with extracting accurate 3D representations of videos in cases where no previous knowledge of the scene or camera is known. In this paper, we present a framework that attempts to compute a dense three dimensional representation of a scene using only the available video sequence. Our proposed system exploits the motion of the camera in order to estimate the relative 3D positions of salient features located in the video frames. Additionally, we incorporate the use of appearance-based models to estimate their relative poses and fit a 3D human model into the reconstructed scenes. We test our method using various video clips obtained from online databases in order to show the feasibility of this approach.