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Mar. 18, 2009 to Mar. 20, 2009
ISBN: 978-1-4244-3858-7
pp: 476-481
Petter Bivall Persson , Department of Science and Technology, Sweden
Matthew D. Cooper , Department of Science and Technology, Sweden
Gunnar E. Host , Department of Science and Technology, Sweden
Lena A.E. Tibell , Department of Clinical and Experimental Medicine, Sweden
Anders Ynnerman , Department of Science and Technology, Link
In this paper we present a history dependent transfer function (HDTF) as a possible approach to enable improved haptic feature detection in high dynamic range (HDR) volume data. The HDTF is a multi-dimensional transfer function that uses the recent force history as a selection criterion to switch between transfer functions, thereby adapting to the explored force range. The HDTF has been evaluated using artificial test data and in a realistic application example, with the HDTF applied to haptic protein-ligand docking. Biochemistry experts performed docking tests, and expressed that the HDTF delivers the expected feedback across a large force magnitude range, conveying both weak attractive and strong repulsive protein-ligand interaction forces. Feature detection tests have been performed with positive results, indicating that the HDTF improves the ability of feature detection in HDR volume data as compared to a static transfer function covering the same range.
Petter Bivall Persson, Matthew D. Cooper, Gunnar E. Host, Lena A.E. Tibell, Anders Ynnerman, "Improved feature detection over large force ranges using history dependent transfer functions", WHC, 2009, World Haptics Conference, World Haptics Conference 2009, pp. 476-481, doi:10.1109/WHC.2009.4810843
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