Although deep learning-based stereo matching approaches have achieved excellent
performance in recent years, it is still a non-trivial task to estimate the uncertainty of the …

Polarization three-dimensional (3D) imaging technology has received extensive attention in
recent years because of its advantages of high accuracy, long detection distance, simplicity …

Stereo matching obtains a depth map called a disparity map that indicates or shows the
positions of the objects in a scene. To estimate a disparity map, the most popular trend …

Traditional semi-global matching (SGM) lacks interaction between scanlines and struggles
to deal with the ambiguity of pixels in homogenous areas. In this paper, we propose a novel …

Depth estimation is an essential tool in obtaining depth information for robotic surgery and
augmented reality technology in the current laparoscopic surgery robot system. Since there …

Supervised learning methods have been used to calculate the stereo matching cost in a lot
of literature. These methods need to learn parameters from public datasets with ground truth …

This paper proposes a new hybrid method between the learning-based and handcrafted
methods for a stereo matching algorithm. The main purpose of the stereo matching algorithm …

English This paper presents a stereo vision system created on a Jetson device with a GPU.
Two cameras attached to the cover are connected to the device. Before using the system …

Stereo reconstruction models trained on small images do not generalize well to high-
resolution data. Training a model on high-resolution image size faces difficulties of data …

Stereo vision algorithms are important building blocks of self-driving applications. The two
primary requirements of a self-driving vehicle are real-time operation and nearly 100 …