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3, 1992 J. Deovre: Probability and statistics for engineering and science. Brooks/Cole, Belmont, CA, 1987 D. Zhang and M. Hebert: Harmonic Maps and Their Applications in Surface Matching. ta S. it Abstract. Size functions are functions from the real plane to the natural numbers useful for describing shapes of objects. They allow to translate the problem of comparing shapes to the problem of comparing functions, that is a much simpler task. In order to perform the comparison between size functions we present a method to measure the energy necessary to deform size functions into each other.
Of Computer Vision, vol. J. Besl: The Free-form Surface Matching Problem. Machine Vision for Threedimensional Scenes. H. J. D. Mckay: A Method for Registration of 3-D Shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, No. 239-256, 1992 Y. Chen and G. Medioni: Object Modeling by Registration of Multiple Range Images. Image Vision Computing, vol. 10, No. 145-155, 1992 R. Bergevin, D. Laurendeau and D. Poussart: Estimating The 3D Rigid Transformation between Two Range Views of A Complex Object.
No two surfaces with different shapes have the same Harmonic Shape Image. This means that Harmonic Shape Images are unique. This is an important property when applied to object recognition. Existence. The existence of harmonic maps from a surface with disc topology to a planar domain ensures the existence of Harmonic Shape Image for a given surface patch D. Robustness. One important issue for surface representations is their robustness with respect to occlusion. In this section, we first explain why Harmonic Shape Images are robust to occlusion and then, using real data, demonstrate the robustness under occlusion.