Author Description

<p>The field of multidimensional data structures is large and growing very quickly. Here, for the first time, is a thorough treatment of multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional datasets.</p> <p>The book includes a thorough introduction; a comprehensive survey to spatial and multidimensional data structures and algorithms; and implementation details for the most useful data structures. Along with the hundreds of worked exercises and hundreds of illustrations, the result is an excellent and valuable reference tool for professionals in many areas, including computer graphics, databases, geographic information systems (GIS), game programming, image processing, pattern recognition, solid modeling, similarity retrieval, and VLSI design.</p> <ul> <li>First comprehensive work on multidimensional data structures available, a thorough and authoritative treatment</li> <li>An algorithmic rather than mathematical approach, with a liberal use of examples that allows the readers to easily see the possible implementation and use</li> <li>Each section includes a large number of exercises and solutions to self-test and confirm the reader's understanding and suggest future directions</li> <li>Written by a well-known authority in the area of spatial data structures who has made many significant contributions to the field</li></ul> <p><b>About the Author</b> Hanan Samet is Professor in the Department of Computer Science at the University of Maryland, and a member of the Center for Automation Research and the Institute for Advanced Computer Studies. He is widely published in the fields of spatial databases and data structures, computer graphics, image databases and image processing, and geographic information systems (GIS), and is considered an authority on the use and design of hierarchical spatial data structures such as the quadtree and octree for geographic information systems, image processing, and com