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We address the problem of reconstructing 3D scenes from a set of unconstrained images. These image sequences can be acquired by a video camera or handheld digital camera without requiring calibration. Our approach does not require any a priori information about the cameras being used. The camera's motion and intrinsic parameters are all unknown. We use a novel combination of advanced computer vision algorithms for feature detection, feature matching, and projection matrix estimation in order to reconstruct a 3D point cloud representing the location of geometric features estimated from input images. In a second step a full 3D model is reconstructed using the projection matrix and a triangulation process. We demonstrate with data sets of different structures obtained under different weather conditions that our algorithm is stable and enables inexperienced users to easily create complex 3D content using a simple consumer level camera.

REALISTIC 3D SCENE RECONSTRUCTION FROM UNSCONSTRAINED AND UNCALIBRATED IMAGES TAKEN WITH A HANDHELD CAMERA