Restricted-Orientation Convexity

Restricted-orientation convexity is the study of geometric objects whose intersections with lines from some fixed set are connected. This notion generalizes standard convexity and several types of nontraditional convexity. We explore the properties of this generalized convexity in multidimensional Euclidean space, describes restricted-orientation analogs of lines, hyperplanes, flats, and halfspaces, and identify major properties of standard convex sets that also hold for restricted-orientation convexity. We then introduce the notion of strong restricted-orientation convexity, which is an alternative generalization of convexity, and show that its properties are also similar to those of standard convexity.

Eugene Fink received his B.S. degree from Mount Allison University (Canada) in 1991, M.S. from the University of Waterloo (Canada) in 1992, and Ph.D. from Carnegie Mellon University (USA) in 1999. He has been an assistant professor in the Computer Science and Engineering Department at the University of South Florida (USA) since 1999. His research interests include computational geometry, artificial intelligence, machine learning, and e-commerce.

Derick Wood received his B.Sc. (1963) and Ph.D. (1968) from the University of Leeds (UK). He was a Postdoctoral Fellow at the Courant Institute, New York University (USA), from 1968 to 1970, and then joined McMaster University (Canada) in 1970. He was a professor at the University of Waterloo (Canada) from 1982 to 1992, at the University of Western Ontario (Canada) from 1992 to 1995, and at the Hong Kong University of Science and Technology since 1995. He has published widely in a number of research areas and written two textbooks, "Theory of Computation" (John Wiley, 1987) and "Data Structures, Algorithms, and Performance" (Addison-Wesley, 1993).