HIPI - Hadoop Image Processing Framework

About

HIPI is designed to provide a clean and simple interface for performing efficient and high-throughput image processing within the Apache Hadoop MapReduce framework. HIPI was created by Sean Arietta, Jason Lawrence, Liu Liu, and Chris Sweeney working together at the University of Virginia Computer Graphics Lab. HIPI has been used in a number of projects and even gained some press.

The initial development of HIPI was supported in part by the National Science Foundation through a Cluster Exploratory (CluE) grant IIS-0844416 ("Image Super-Resolution using Trillions of Examples") and with resources generously made available by IBM and Google.

Core Team

Liu Liu is a former undergraduate student at the University of Virginia. He now works at Facebook and has made numerous contributions to the popular OpenCV library. Chris Sweeney Chris Sweeney is a former undergraduate student at the University of Virginia. He is now a graduate student at the University of California at Santa Barbara where his research investigates various topics in computer vision including SLAM systems and 3D scene reconstruction.
Sean Arietta Sean Arietta is former graduate student at the University of Virginia. He is now a PhD student at the University of California at Berkeley. Sean's research focuses on applications of Internet-scale image processing. Jason Lawrence Jason Lawrence is associate professor in the Department of Computer Science at the University of Virginia. In addition to large-scale image processing, his research interests include real-time and global illumination rendering algorithms and methods for general appearance capture.
Zack Verham is a current undergraduate student at the University of Virginia. He will be graduating in May of 2015 and will be entering a Master's program at the University of Virginia with a continued focus in image processing.