Accelerated algorithms for image processing and computer vision

Editor: Volodymyr Kindratenko

Background Information

Accelerated algorithms for image processing and computer vision, to be published by Springer, will contain a collection of articles on fundamental image processing and computer vision methods adapted for Graphics Processing Units (GPUs), Intel Xeon Phi, and other types of computational accelerators. In recent years, substantial efforts were undertaken to adapt many such algorithms for newly-emerged massively-parallel accelerator-based systems. The book is envisioned as a consolidation of such work into a single volume covering widely used methods and techniques. Each chapter will be written by authors working on a specific group of methods. It will provide mathematical background, parallel algorithm, and implementation details leading to reusable, adaptable, and scalable code fragments. The book will serve as an implementation manual for many image processing and analysis algorithms providing valuable insights into parallelization strategies for GPUs and other accelerators as well as ready-to-use code fragments with a broad appeal to both developers and researchers interested in image computing.

Call for Contributions

Researchers working on the development and implementation of methods for image and video processing and analysis on computational accelerators, such as GPUs, Xeon Phi, FPGAs, are invited to submit their work for consideration for inclusion in the book. Articles on the following broad topics are solicited: Authors interested in contributing to this volume are asked to submit a short proposal via email to the Editor by June 1, 2016. Authors of the accepted/invited chapters are expected to write and submit to the editor completed chapters by September 1, 2016. For more details, contact the Editor at kindrtnk@illinois.edu.

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