# OpenCL-based FPGA accelerator for disparity map generation with stereoscopic event cameras

## TL;DR

This paper develops FPGA accelerators for disparity map generation using stereoscopic event cameras, demonstrating over 8x speedup with simple code modifications, advancing hardware support for event-based vision algorithms.

## Contribution

It introduces FPGA-based accelerators for a stereo matching algorithm with event cameras, showcasing flexible design testing and significant performance improvements.

## Key findings

- Achieved over 8x speedup in disparity map generation
- Implemented multiple FPGA accelerator designs using OpenCL
- Demonstrated ease of testing different accelerator configurations

## Abstract

Although event-based cameras are already commercially available. Vision algorithms based on them are still not common. As a consequence, there are few Hardware Accelerators for them. In this work we present some experiments to create FPGA accelerators for a well-known vision algorithm using event-based cameras. We present a stereo matching algorithm to create a stream of disparity events disparity map and implement several accelerators using the Intel FPGA OpenCL tool-chain. The results show that multiple designs can be easily tested and that a performance speedup of more than 8x can be achieved with simple code transformations.

---
Source: https://tomesphere.com/paper/1903.03509