Hot curves for modelling and recognition of smooth curved 3D objects

摘要

Major advances in object representation, modelling and matching are required to develop vision systems capable of recognizing complex curved 3D objects observed in monocular images from a large database of models. In this paper, we propose to represent smooth curved 3D shapes by a set of curves where the surface admits high-order tangents. These HOT curves have two remarkable properties: they determine the structure of the image contours and its catastrophic changes, and there is a natural correspondence between two of them (parabolic and limiting bitangent curves) and monocular image features (contour inflections and bitangents). We present a method for automatically constructing these two curves from continuous sequences of video images and describe an approach to object recognition using viewpoint-dependent monocular image features as indexes into a database of models and as a basis for pose estimation. We have implemented both algorithms and present results obtained from real images. We briefly discuss the construction of the whole set of HOT curves and its application to aspect graph construction from image data.