Dense 3-D reconstruction of an outdoor scene, by hundreds-baseline stereo using a hand-held video camera

Three-dimensional (3-D) models of outdoor scenes are widely used for object recognition, navigation, mixed reality, and so on. Because such models are often made manually with high costs, automatic and dense 3-D reconstruction is widely investigated. In related work, a dense 3-D model is generated by using a stereo method. However these methods cannot use several hundreds images together for dense depth estimation because it is difficult to accurately calibrate a large number of cameras. In this paper we propose a dense 3-D reconstruction method that first estimates extrinsic camera parameters of a hand-held video camera, and then reconstructs a dense 3-D model of a scene. We can acquire a model of the scene accurately by using several hundreds input images.