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In the context of 2D/3D registration, this paper introduces an approach thatallows to match features detected in two different modalities: photographs and3D models, by using a common 2D reprensentation. More precisely, 2D images arematched with a set of depth images, representing the 3D model. Afterintroducing the concept of curvilinear saliency, related to curvatureestimation, we propose a new ridge and valley detector for depth imagesrendered from 3D model. A variant of this detector is adapted to photographs,in particular by applying it in multi-scale and by combining this featuredetector with the principle of focus curves. Finally, a registration algorithmfor determining the correct viewpoint of the 3D model and thus the pose isproposed. It is based on using histogram of gradients features adapted to thefeatures manipulated in 2D and in 3D, and the introduction of repeatabilityscores. The results presented highlight the quality of the features detected,in term of repeatability, and also the interest of the approach forregistration and pose estimation.

Using Curvilinear Features in Focus for Registering a Single Image to a 3D Object