ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Multiscale Symmetry Detection in Scalar Fields by Clustering Contours

Thomas, Dilip Mathew and Natarajan, Vijay (2014) Multiscale Symmetry Detection in Scalar Fields by Clustering Contours. In: IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 20 (12). pp. 2427-2436.

[img] PDF
iee_tra_vis_com_gra_20-12_2427_2014.pdf - Published Version
Restricted to Registered users only

Download (794Kb) | Request a copy
Official URL: http://dx.doi.org/ 10.1109/TVCG.2014.2346332

Abstract

The complexity in visualizing volumetric data often limits the scope of direct exploration of scalar fields. Isocontour extraction is a popular method for exploring scalar fields because of its simplicity in presenting features in the data. In this paper, we present a novel representation of contours with the aim of studying the similarity relationship between the contours. The representation maps contours to points in a high-dimensional transformation-invariant descriptor space. We leverage the power of this representation to design a clustering based algorithm for detecting symmetric regions in a scalar field. Symmetry detection is a challenging problem because it demands both segmentation of the data and identification of transformation invariant segments. While the former task can be addressed using topological analysis of scalar fields, the latter requires geometry based solutions. Our approach combines the two by utilizing the contour tree for segmenting the data and the descriptor space for determining transformation invariance. We discuss two applications, query driven exploration and asymmetry visualization, that demonstrate the effectiveness of the approach.

Item Type: Journal Article
Related URLs:
Additional Information: Copyright for this article belongs to the IEEE COMPUTER SOC, 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA
Keywords: Scalar field visualization; symmetry detection; contour tree; data exploration
Department/Centre: Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)
Date Deposited: 26 Dec 2014 06:39
Last Modified: 26 Dec 2014 06:39
URI: http://eprints.iisc.ernet.in/id/eprint/50509

Actions (login required)

View Item View Item