TY - CHAP
T1 - Characterizing 3D shapes using fractal dimension
AU - Backes, André Ricardo
AU - Eler, Danilo Medeiros
AU - Minghim, Rosane
AU - Bruno, Odemir Martinez
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
KW - 3D shape descriptor
KW - complexity
KW - Fractal dimension
UR - https://www.scopus.com/pages/publications/78649915313
U2 - 10.1007/978-3-642-16687-7_7
DO - 10.1007/978-3-642-16687-7_7
M3 - Chapter
AN - SCOPUS:78649915313
SN - 3642166865
SN - 9783642166860
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 14
EP - 21
BT - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 15th Iberoamerican Congress on Pattern Recognition, CIARP 2010, Proceedings
T2 - 15th Iberoamerican Congress on Pattern Recognition, CIARP 2010
Y2 - 8 November 2010 through 11 November 2010
ER -