Abstract: Accurate segmentation of 3D point clouds in indoor scenes remains a challenging task, often hindered by the labor-intensive nature of data annotation. While weakly supervised learning ...
Abstract: Visual-inertial odometry (VIO) is widely used in autonomous driving, robots, and drones in global navigation satellite system (GNSS)-denied environments. Current VIO methods primarily rely ...
Abstract: This paper primarily explores safety perception challenges in substation operation and maintenance. First, we propose a cross-scenario safety perception method based on the fusion of visual ...
A recreation of the classic Visual Basic 6 IDE and language in C# using Avalonia. This is a fun, toy project with no commercial intent. All rights to the Visual Basic name, icons, and graphics belong ...
STEVENS POINT, Wis. – The Stevens Point Plan Commission and Historic Preservation Commission reviewed a proposed $15 million city hall complex on Ellis Street on Monday night. According to our ...
Abstract: Accurate localization constitutes a fundamental building block of any autonomous system. In this article, we focus on stereo cameras and present a novel approach, dubbed SOFT2, that is ...
Abstract: For robots operating in the GPS-denied environment, visual inertial simultaneous localization and mapping (VI-SLAM) is a popular solution for localization. However, under challenging ...
Abstract: This article proposes a monocular point-line visual-inertial odometry (VIO) with line filtering and fast line matching (FLM PL-VIO), improving the localization accuracy and robustness.
Abstract: Local minima are a well-known drawback of image-based visual servoing systems. Up to now, there were no formal guarantees on their number, or even their existence, according to the ...
Abstract: Mainstream visual-inertial SLAM systems use point features for motion estimation and localization. However, point features do not perform well in scenes such as weak texture and motion blur.
Abstract: In this letter, we introduce HPGS-SLAM, a real-time RGB-D SLAM system guided by hybrid point features (combining traditional and learned point features), enabling high-precision tracking and ...
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