38 citations · 62 across the 5 of their papers we have counts for
5 papers
Deep Learning for Spacecraft Pose Estimation from Photorealistic Rendering
Pedro F. Proenca, Yang Gao
On-orbit proximity operations in space rendezvous, docking and debris removal require precise and robust 6D pose estimation under a wide range of lighting conditions and against hi…
Fast Cylinder and Plane Extraction from Depth Cameras for Visual Odometry
Pedro F. Proença, Yang Gao
This paper presents CAPE, a method to extract planes and cylinder segments from organized point clouds, which processes 640x480 depth images on a single CPU core at an average of 3…
SPLODE: Semi-Probabilistic Point and Line Odometry with Depth Estimation from RGB-D Camera Motion
Pedro F. Proença, Yang Gao
Active depth cameras suffer from several limitations, which cause incomplete and noisy depth maps, and may consequently affect the performance of RGB-D Odometry. To address this is…
Probabilistic RGB-D Odometry based on Points, Lines and Planes Under Depth Uncertainty
Pedro F. Proenca, Yang Gao
This work proposes a robust visual odometry method for structured environments that combines point features with line and plane segments, extracted through an RGB-D camera. Noisy d…
Probabilistic Combination of Noisy Points and Planes for RGB-D Odometry
Pedro F. Proença, Yang Gao
This work proposes a visual odometry method that combines points and plane primitives, extracted from a noisy depth camera. Depth measurement uncertainty is modelled and propagated…