In recent years, with the advent of cheap and accurate RGBD (RGB plus Depth) active sensors like the Microsoft Kinect and devices based on time-of-flight (ToF) technology, there has been increasing interest in 3D-based applications. At the same time, several effective improvements to passive stereo vision algorithms have been proposed in the literature. Despite these facts and the frequent deployment of stereo vision for many research activities, it is often perceived as a bulky and expensive technology not well suited to consumer applications. In this paper, we will review a subset of state-of-the-art stereo vision algorithms that have the potential to fit a target computing architecture based on low-cost field-programmable gate arrays (FPGAs), without additional external devices (e.g., FIFOs, DDR memories, etc.). Mapping these algorithms into a similar low-power, low-cost architecture would make RGBD sensors based on stereo vision suitable to a wider class of application scenarios currently not addressed by this technology.

S. Mattoccia (2013). Stereo Vision Algorithms for FPGAs. PIscataway, NJ : IEEE [10.1109/CVPRW.2013.96].

Stereo Vision Algorithms for FPGAs

MATTOCCIA, STEFANO
2013

Abstract

In recent years, with the advent of cheap and accurate RGBD (RGB plus Depth) active sensors like the Microsoft Kinect and devices based on time-of-flight (ToF) technology, there has been increasing interest in 3D-based applications. At the same time, several effective improvements to passive stereo vision algorithms have been proposed in the literature. Despite these facts and the frequent deployment of stereo vision for many research activities, it is often perceived as a bulky and expensive technology not well suited to consumer applications. In this paper, we will review a subset of state-of-the-art stereo vision algorithms that have the potential to fit a target computing architecture based on low-cost field-programmable gate arrays (FPGAs), without additional external devices (e.g., FIFOs, DDR memories, etc.). Mapping these algorithms into a similar low-power, low-cost architecture would make RGBD sensors based on stereo vision suitable to a wider class of application scenarios currently not addressed by this technology.
2013
Computer Vision and Pattern Recognition Workshops (CVPRW), 2013 IEEE Conference on
636
641
S. Mattoccia (2013). Stereo Vision Algorithms for FPGAs. PIscataway, NJ : IEEE [10.1109/CVPRW.2013.96].
S. Mattoccia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/398119
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