FOCus Introduction
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The document discusses a project to implement computer vision algorithms using OpenCV on an FPGA. Specifically, it focuses on optimizing an image stitching algorithm to reduce processing time and improve quality. It identifies using an Intel Atom processor board paired with an AlphaData Kintex Ultrascale FPGA to maximize parallelization opportunities for image manipulation algorithms. The goal is to overcome speed limitations of the Intel Atom by offloading work to the FPGA, which will involve analyzing and optimizing the OpenCV stitching algorithm for parallel hardware implementation.
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FOCus Introduction
- 1. Andrea Milanta (andrea.milanta@mail.polimi.it) Guido Muscioni (guido.muscioni@mail.polimi.it) Matteo Foglio (matteo.foglio@mail.polimi.it) Computer vision implementing OpenCV on FPGA 1
- 2. Context 2 What is Computer Vision? “Humans use their eyes and their brains to see and visually sense the world around them. Computer vision is the science that aims to give a similar, if not better, capability to a machine or computer.”
- 3. Context 3 The project has been provided by Bottega52, a technological startup that works also in the field of biomedical image processing.
- 4. Context 3 The project has been provided by Bottega52, a technological startup that works also in the field of biomedical image processing. We will focus on the stitching algorithm that merges multiple photos in a single one.
- 6. Image stitching 1. Capturing 2. Ordering 4
- 7. Image stitching 1. Capturing 2. Ordering 3. Merging 4
- 8. Stitching requires a lot of time Rationals Quality is important 5
- 9. reduce Time improve Quality Stitching requires a lot of time Rationals + Quality is important = 5
- 10. Hardware identification 6 Intel base board • Standard for biomedical embedded devices • Low price Intel Atom E8000
- 11. Hardware identification 6 AlphaData Kintex Ultrascale Intel base board • Standard for biomedical embedded devices • Low price Intel Atom E8000 • Maximum exploit of embarassingly parallel algorithms, such as those for image manipulation FPGA
- 12. Hardware identification The goal of FOCus project is to overcome the limit of Intel Atom processor via FPGA technology 6 AlphaData Kintex Ultrascale Intel base board • Standard for biomedical embedded devices • Low price Intel Atom E8000 • Maximum exploit of embarassingly parallel algorithms, such as those for image manipulation FPGA
- 13. How to do it Algorithm analysis Parallelism optimization OpenCV Stitching algorithm 7
- 14. How to do it Algorithm analysis Parallelism optimization FPGA Intel board OpenCV Stitching algorithm Mapping algorithm on hardware resources 7
- 15. Questions? Guido Muscioni Bachelor in Computer Science guido.muscioni@mail.polimi.it Andrea Milanta Bachelor in Computer Science andrea.milanta@mail.polimi.it FOCus at NECST facebook.com/FOCusatNECST/ FOCusAtNECST slideshare.net/FOCusAtNECST/ @FOCusAtNECST twitter.com/FOCusAtNECST 8 Matteo Foglio Bachelor in Computer Science matteo.foglio@mail.polimi.it Contact us bitbucket.org/necst/xohw17_f ocus_public
Editor's Notes
- Non è chiarissimo però è il massimo.
- Timing constraints