Rapid preconditioning of data for accelerating convex hull algorithms

Downloads

1 Wan, Z., Sun, M., and Jiang, J.: ‘Automatically fast determining of feature number for ranking-based feature selection’, Electron. Lett., 2012, 48, (23), pp. 23–24 2 Preparata, F., and Shamos, M.: ‘Computational geometry: An introduction’ (Springer, New York, 1985), Chap. 3 3 Melkman, A.: ‘On-line construction of the convex hull of a simple polyline’, Inf. Process. Lett.,1987, 25, (1), pp. 11–12 4 Akl, S.G., and Toussaint, G.T.: ‘A fast convex hull algorithm’, Inf. Process. Lett.,1978, 7, (6), pp. 219–222 5 Tang, M., Zhao, J., Tong, R., and Manocha, D.: ‘Full GPU accelerated convex hull computation’, Comput. Graph., 2012, 36, (5), pp. 498–506 6 Teuhola, J.: ‘A compression method for clustered bit-vectors’, Inf. Process. Lett., 1978, 7, (6), pp. 308–311 7 Kernigham, B.W., and Ritchie, D.: ‘The C Programming Language’ (Prentice-Hall, Upper Saddle River, NJ, 1978, 2nd edn) 8 Megson, G.M., and Cadenas, J.: ‘A rank-based convex hull method for dense data sets’ (arXiv:1301.4809 [cs.CG]) 9 Sellers, W.I., et al.: ‘Minimum convex hull mass estimation of complete mounted skeletons’, Biol. Lett., 2012, doi: 10.1098/rsbl.2012.0263