Computer Vision

A single-camera stereo omnidirectional system (SOS) is applied for estimating egomotion in real-world environments.

We present the advantages of a single-camera stereo omnidirectional system (SOS) in estimating egomotion in real-world environments.

We explore low-cost solutions for efficiently improving the 3D pose estimation problem of a single omnidirectional camera moving in an unfamiliar environment.

We present direct multichannel tracking, an algorithm for tracking the pose of a monocular camera (visual odometry) using high-dimensional features in a direct image alignment framework.

GUMS is a complete projection model for omnidirectional stereo vision systems. GUMS is based on the existing generalized unified model (GUM), which we extend for fixed baseline sensors.

We describe the design and 3D sensing performance of an omnidirectional stereo (omnistereo) vision system applied to Micro Aerial Vehicles (MAVs).

We present an on-board navigation system for Micro Aerial Vehicles (MAV) based on information provided by a visual odometry algorithm processing data from an RGB-D camera.

A 6-degree-of-freedom (6-DoF) pose localization method for a monocular camera in a 3D point-cloud dense map prebuilt by an RGB-D sensor.

We introduce a catadioptric single-camera omnistereo vision system that uses a pair of custom-designed mirrors (in a folded configuration) satisfying the single view point (SVP) property as a good solution to the perception challenge of MAVs.

We design a novel 'folded' spherical catadioptric rig (formed by two coaxially-aligned spherical mirrors of distinct radii and a single perspective camera) to recover near-spherical range panoramas.