This paper aims at detecting obstacles using a single camera in an unknown three dimensional world, for 3D motion of an unmanned air vehicle. Obstacle detection is a pre-requisite for collision-free motion of a UAV through 3D space. Most research towards vision based obstacle detection and avoidance has been done for 2D planar motion of ground robots and using active sensors like laser range finders, sonar, radar etc. Passive camera based research has mostly been done, either using stereo vision (multiple cameras) or, by developing a prior expectation map of the world and its comparison with the new image data. In this paper, an attempt has been made to find a 3D solution of the obstacle detection problem using a single camera in an unknown world. The equations developed and the simulations results presented here, show that a 3D model of the scene can be generated from 2D image information from a single camera flying through a very small arc of lateral flight around the object, without the need of capturing images from all sides as in a typical 'structures from motion' problem. The forward flight simulation results show that the depth extracted from forward motion is in fact usable for large part of the image, which is a significant contribution of this work.