Abstract
We propose a coarse registration method of range images using both geometric and photometric features. The framework of existing methods using multiple features first defines a single similarity distance summing up each feature based evaluations, and then minimizes the distance between range images for registration. In contrast, we formulate registration as a graph-based optimization problem, where we independently evaluate geometric feature and photometric feature and consider only the order of point-to-point matching quality. We then find as large consistent matching as possible in the sense of the matching-quality order. This is solved as one global combinatorial optimization problem. Our method thus does not require any good initial estimation and, at the same time, guarantees that the global solution is achieved.
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Shimizu, I., Sugimoto, A., Šára, R. (2007). Graph-Based Range Image Registration Combining Geometric and Photometric Features. In: Ersbøll, B.K., Pedersen, K.S. (eds) Image Analysis. SCIA 2007. Lecture Notes in Computer Science, vol 4522. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73040-8_55
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DOI: https://doi.org/10.1007/978-3-540-73040-8_55
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