Level: Beginner

Prerequisites: Familiarity with computer terminology and some programming experience

Presentation Language: English

Intended Audience: Practitioners working in computer graphics and computer vision will be given a different perspective on data structures found to be useful in most applications. Game developers and technical managers will appreciate the presentation and methods described herein.

Organizer: Hanan Samet (http://www.cs.umd.edu/~hjs) is a Distinguished University Professor of Computer Science at the University of Maryland where he researches using hierarchical data structures for GIS and spatial and image databases. He wrote "Foundations of Multidimensional and Metric Data Structures," Morgan-Kaufmann, 2006 and the first two texts in the field "Design and Analysis of Spatial Data Structures" and "Applications of Spatial Data Structures: Computer Graphics, Image Processing and GIS". His Ph.D is from Stanford. He recieved the 2011 ACM Paris Kanellakis Theory and Practice, 2014 Computer Society McDowell, and the 2009 UCGIS Research Awards.

Speaker(s):
Hanan Samet, University of Maryland

Summary: We show how to represent spatial data using techniques that sort it.
They include quadtrees, octrees, and bounding volume hierarchies and
are rooted in the intersection between computer vision and graphics.
We focus on building these representations and on finding nearest
neighbors which is critical when using machine learning method