Stereo Vision Algorithms Suited to Constrained FPGA Cameras - Advances in Embedded Computer Vision - page 104

Chapter 5
Stereo Vision Algorithms Suited to Constrained
FPGA Cameras

Stefano Mattoccia

Abstract The advent of cheap RGBD active 3D sensors, such as those based on
structured light (e.g., the Microsoft Kinect) or those based on time-of-flight technol-
ogy, has significantly increased the interest in computer vision applications based
on depth data that, in most cases, enables higher robustness compared to solutions
based on traditional 2D images. Unfortunately, active techniques are quite noisy
or even completely useless in outdoor environments (in particular under sunlight).
An effective and well-known technique to infer depth suited to indoor and outdoor
environments is passive stereo vision. Nevertheless, despite the frequent deployment
of this technology in many research projects since the 1960s, stereo vision is often
perceived, especially in consumer applications, as an expensive technology due to
its high demanding computation requirements. In this paper, we will review a subset
of state-of-the-art stereo vision algorithms that have the potential to fit with a basic
computing architecture made of a low-cost field-programmable gate arrays (FPGAs),
without additional external devices (e.g., FIFOs, DDR memories, etc.) excluding a
USB or GigaEthernet communication controller. Compared tomore complex designs
based on expensive FPGAs coupled with additional external memory devices, clear
advantages of the outlined simplified computing architecture are the reduced design
and manufacturing costs as well as the reduced power consumption. Another signif-
icant advantage consists in better code portability as well as in improved robustness
with respect to obsolescence of electronic devices being almost the whole design
self-contained into the FPGA logic. On the other hand, mapping stereo vision algo-
rithms into a similar low-power, low-cost architecture poses a very challenging task
and only a subset of existing algorithms appropriately modified are suited to this con-
strained computing platform. Nevertheless, we believe that devices based on such
a proposed simplified computing architecture would make RGBD sensors based on
stereo vision suitable to a wider class of application scenarios not yet fully addressed
by this technology.

( B )
Department of Computer Science and Engineering, University of Bologna, Bologna, Italy
e-mail: [e-mail]

S. Mattoccia