We present a novel approach to pose estimation and model-based recognition of specular objects in difficult viewing conditions, such as low illumination, cluttered background, large highlights, and shadows that appear on the object of interest. In such challenging conditions, conventional features are unreliable. We show that under the assumption of a dominant light source, specular highlights produced by a known object can be used to establish correspondence between its image and the 3D model, and to verify the hypothesized pose and the identity of the object. Previous methods that use highlights for recognition make limiting assumptions such as known pose, scene-dependent calibration, simple shape, etc. The proposed method can efficiently recognize free-form specular objects in arbitrary pose and under unknown lighting direction. It uses only a single image of the object as its input and outputs object identity and the full pose. We have performed extensive experiments for both recognition and pose estimation accuracy on synthetic images and on real indoor and outdoor images.

We address the problem of 2D-3D pose estimation in difficult viewing conditions, such as low illumination, cluttered background, and large highlights and shadows that appear on the object of interest. In such challenging conditions conventional features used for establishing correspondence are unreliable. We show that under the assumption of a dominant light source, specular highlights produced by a known object can be used to establish correspondence between its image and the 3D model, and to verify the hypothesized pose. These ideas are incorporated in an efficient method for pose estimation from a monocular image of an object using only highlights produced by the object as its input. The proposed method uses no knowledge of lighting direction and no calibration object for estimating the lighting in the scene. The evaluation of the method shows good accuracy on numerous synthetic images and good robustness on real images of complex, shiny objects, with shadows and difficult backgrounds.