This paper describes a new architecture and the corresponding implementation of a stereo
vision system that covers the entire stereo vision process including noise reduction …

Low-level computer vision algorithms have extreme computational requirements. In this
work, we compare two real-time architectures developed using FPGA and GPU devices for …

Phase shifting structured light illumination for range sensing involves projecting a set of
grating patterns where accuracy is determined, in part, by the number of stripes. However …

Loopy belief propagation (BP) is an effective solution for assigning labels to the nodes of a
graphical model such as the Markov random field (MRF), but it requires high memory …

The proposed work presents a highly parallel architecture for motion estimation. Our system
implements the well-known Lucas and Kanade algorithm with the multi-scale extension for …

Phase-based optical flow algorithms are characterized by high precision and robustness,
but also by high computational requirements. Using the CUDA platform, we have …

Stereo Vision, a technique aimed at inferring depth information from stereo images, has
been used in a wide range of computer vision applications, with real-time requirements in …

Low-level vision tasks pose an outstanding challenge in terms of computational effort: pixel-
wise operations require high-performance architectures to achieve real-time processing …

In this work, we present a real-time implementation of a stereo algorithm on field-
programmable gate array (FPGA). The approach is a phase-based model that allows …

Many vision applications require high-accuracy dense disparity maps in real time. Due to the
complexity of the matching process, most real-time stereo applications rely on local …