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Curvature determination in range images: new methods and comparison study

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Abstract

A study of methods that determine surface curvature in real and synthetic range images is considered here. Four new determination methods are introduced (two convolution-based and two spline-based). These new methods, as well as a number of existing determination methods, are comparatively evaluated in terms of their (1) accuracy and (2) computational performance (i.e., run time). Their behavior in two common but challenging multimedia tasks (surface rendering and object discrimination based in whole or part on curvature determination) is also considered. Our evaluations also include an analysis of (1) which methods are most suitable for application in particular scenarios and (2) behavior of the methods with respect to parameter settings. One of the considered use cases includes application to consumer-grade Kinect sensor data.

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We acknowledge comments of a review team that were used to improve this paper.

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  1. University of Alabama in Huntsville, 301 Sparkman Drive, Huntsville, Alabama, 35899, USA

    Jacob D. Hauenstein & Timothy S. Newman

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Hauenstein, J.D., Newman, T.S. Curvature determination in range images: new methods and comparison study. Multimed Tools Appl 78, 9247–9273 (2019). https://doi.org/10.1007/s11042-018-6363-0

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