Implementation of a Depth from Light Field Algorithm on FPGA

Abstract

A light field is a four-dimensional function that grabs the intensity of light rays traversing an empty space at each point. The light field can be captured using devices designed specifically for this purpose and it allows one to extract depth information about the scene. Most light-field algorithms require a huge amount of processing power. Fortunately, in recent years, parallel hardware has evolved and enables such volumes of data to be processed. Field programmable gate arrays are one such option. In this paper, we propose two hardware designs that share a common construction block to compute a disparity map from light-field data. The first design employs serial data input into the hardware, while the second employs view parallel input. These designs focus on performing calculations during data read-in and producing results only a few clock cycles after read-in. Several experiments were conducted. First, the influence of using fixed-point arithmetic on accuracy was tested using synthetic light-field data. Also tests on actual light field data were performed. The performance was compared to that of a CPU, as well as an embedded processor. Our designs showed similar performance to the former and outperformed the latter. For further comparison, we also discuss the performance difference between our designs and other designs described in the literature.

Design of an FPGA Hardware Optimizing the Performance and Power Consumption of a Plenoptic Camera Depth Estimation Algorithm

“…A small number of researchers used FPGA for the depth estimation [32], and disparity [33] calculation algorithms based on plenoptic camera. However, these algorithms do not work directly on the raw data captured by the plenoptic camera.…”

FPGA Hardware Design for Plenoptic 3D Image Processing Algorithm Targeting a Mobile Application

“…In literature, few researchers [8,9] proposed FPGA accelerators for plenoptic camera based systems, but they only deal with the 2D refocusing algorithms. A small number of researchers used FPGA for the depth estimation [10], and disparity [11] calculation algorithms, which, however, do not work directly on the raw data captured by the plenoptic camera. Latter's approach uses multiple focused images separated by some distance, which can either be obtained by multiple cameras or by generating several images with different perspectives.…”