R Paul Beveridge

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The CSU Face Identification Evaluation System provides standard face recognition algorithms and standard statistical methods for comparing face recognition algorithms. This document describes Version 5.0 the Colorado State University (CSU) Face Identification Evaluation System. The system includes standardized image pre-processing software, four distinct(More)
Preface In September of 2003 a one week meeting of the authors 1 of this document was held near Colch-ester, funded by EU IST project 1999-14159, to discuss best practices in the design and evaluation of computer vision systems. The main aim of the meeting was the generation of this document, an attempt by the authors to relate common problems and(More)
ACKNOWLEDGMENTS I would like to thank my advisor, Ruzena Bajcsy, for her guidance and enthusiasm, and for providing the excellent resources of the GRASP Lab. I would like to thank my committee (Dimitri Metaxas, Max Mintz, Chuck Thorpe, and Greg Provan), whose comments have improved this dissertation. The followin individuals and organizations made images(More)
A socio-spatial understanding of water politics: Tracing topologies of water reuse. ABSTRACT: Much social science literature on water reuse focuses on problems of acceptance and economic problems, while the spatial and political dimensions remain under-researched. This paper addresses this deficit by reformulating the issue in terms of sociospatial politics(More)
grew substantially over BTAS 07, both in number of submissions and in number of attendees, and this conference series has quickly established itself as the premier research conference focused on biometric technologies. See the conference web page http://www.cse.nd.edu/BTAS_10 for information about the next BTAS conference, as well as for links to more(More)
Sediment trend analysis (STA) is a technique that determines the net patterns of sediment movement and their dynamic behavior or stability. The data required are the complete particle size distributions obtained from bottom grab samples collected in a regular grid over the area of interest. Appendix 1 provides the particular details of how STA is(More)
ACKNOWLEDGMENTS I consider it a great privilege to have been a member of the computer vision group at the University of Massachusetts these past eight years. My thesis advisor, Al Hanson, patiently gave me what I needed to succeed: freedom, opportunity, guidance and encouragement. For this, I am deeply grateful. With Al, Ed Riseman built a computer vision(More)
to the memory of my mother Acknowledgments This dissertation would not have been possible without the help of many people. First, I would like to thank my committee for their many helpful comments and suggestions. Speciically, Al Hanson who taught me about computer vision, Wayne Burleson who taught me about VLSI, and Don Towsley who taught me about(More)