Developments in techniques for modeling and digitizing have made the use of 3D models popular to a large number of new applications. With the diffusion and spreading of 3D models employment, the demand for efficient search and retrieval methods is high. Researchers have dedicated effort to investigate and overcome the problem of 3D shape retrieval. In this work, we propose a new way to employ shape complexity analysis methods, such as the fractal dimension, to perform the 3D shape characterization for those purposes. This approach is described and experimental results are performed on a 3D models data set. We also compare the technique to two other known methods for 3D model description, reported in literature, namely shape histograms and shape distributions. The technique presented here has performed considerably better than any of the others in the experiments. © 2010 Springer-Verlag.
CITATION STYLE
Backes, A. R., Eler, D. M., Minghim, R., & Bruno, O. M. (2010). Characterizing 3D shapes using fractal dimension. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6419 LNCS, pp. 14–21). https://doi.org/10.1007/978-3-642-16687-7_7
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