A Study on Topological Descriptors for the Analysis of 3D Surface Texture
arXiv:1710.10662 · doi:10.1016/j.cviu.2017.10.012
Abstract
Methods from computational topology are becoming more and more popular in computer vision and have shown to improve the state-of-the-art in several tasks. In this paper, we investigate the applicability of topological descriptors in the context of 3D surface analysis for the classification of different surface textures. We present a comprehensive study on topological descriptors, investigate their robustness and expressiveness and compare them with state-of-the-art methods including Convolutional Neural Networks (CNNs). Results show that class-specific information is reflected well in topological descriptors. The investigated descriptors can directly compete with non-topological descriptors and capture complementary information. As a consequence they improve the state-of-the-art when combined with non-topological descriptors.
Preprint of Article "A Study on Topological Descriptors for the Analysis of 3D Surface Texture" in Elsevier Journal on Computer Vision and Image Understanding (CVIU): https://doi.org/10.1016/j.cviu.2017.10.012, 17 Pages, 19 Figures, 4 Tables