Jugesh Sundram — accepted AI-conference papers

2021

Real-Time Outdoor Illumination Estimation for Camera Tracking in Indoor Environments

Michael Krawez, Tim Caselitz, Jugesh Sundram, Mark Van Loock, Wolfram Burgard

RA-L 2021

Dynamic illumination is a challenging problem for visual robot localization and tracking. In indoor environments, the main source of light during the day is outdoor illumination. We propose a method that estimates the appearance of an indoor scene in real-time based on a reflectance map and the curr

Cited by 2 Source ↗Scholar ↗

2020

Camera Tracking in Lighting Adaptable Maps of Indoor Environments

Tim Caselitz, Michael Krawez, Jugesh Sundram, Mark Van Loock, Wolfram Burgard

ICRA 2020poster

Tracking the pose of a camera is at the core of visual localization methods used in many applications. As the observations of a camera are inherently affected by lighting, it has always been a challenge for these methods to cope with varying lighting conditions. Thus far, this issue has mainly been…

Cited by 10 Source ↗Scholar ↗