Efficient Monocular 3D Reconstruction from Segments for Visual Navigation in Structured Environments

We present an algorithm for performing real time 3D reconstructions of indoor scenes from a single image. The technique has been successfully used in indoor robot visual navigation applications. To solve the depth ambiguity inherent to the process of image formation, the procedure interprets the scene in terms of a set of vertical planes in arbitrary orientations (e.g. walls and doors) lying on a common horizontal plane (the floor). Interpretation is based on a zone classification algorithm that divides the image into a set of disjoint patches, each one belonging to a different plane. In order to make the reconstruction possible in real time, we use a very fast feature extraction algorithm based on robust extraction of the most salient segments of the scene, augmented with local color information. The extracted segments help in both the construction of the zone classification machine and the posterior 3D reconstruction, which is in turn based on a powerful single image projective geometry result