Ethan Elms

High-Throughput Event-Based Feature Detection and Tracking on an Embedded CPU

Ethan Elms, Yasir Latif, Tat-Jun Chin

au (code pays fourni par la source)

Event-Based Spinning Object SLAM

Ethan Elms, Yasir Latif, Tat-Jun Chin

Event sensors offer high temporal resolution and high dynamic range visual sensing which makes them appealing for visual simultaneous localization and mapping (VSLAM). In this work, we investigate event-based VSLAM for the scenario where a static event camera observes an object that …

au (code pays fourni par la source)

Event-based Structure-from-Orbit

Ethan Elms, Yasir Latif, Tae Park, Tat-Jun Chin

Event sensors offer high temporal resolution visual sensing, which makes them ideal for perceiving fast visual phe-nomena without suffering from motion blur. Certain applications in robotics and vision-based navigation require 3D perception of an object undergoing circular or spinning motion in front …

au, us (code pays fourni par la source)

Event-based Structure-from-Orbit

Ethan Elms, Yasir Latif, Tat-Jun Chin

Dataset used in the paper "Event-based Structure-from-Orbit", for the purpose of sparse point cloud reconstruction of a spinning object. The dataset consists of six objects rotating at three speeds, being viewed by a static event camera from four different perspectives. For each …

au, us (code pays fourni par la source)

Towards Bridging the Space Domain Gap for Satellite Pose Estimation using Event Sensing

Mohsi Jawaid, Ethan Elms, Yasir Latif, Tat-Jun Chin

Deep models trained using synthetic data require domain adaptation to bridge the gap between the simulation and target environments. State-of-the-art domain adaptation methods often demand sufficient amounts of (unlabelled) data from the target domain. However, this need is difficult to fulfil when …

SEENIC: dataset for Spacecraft posE Estimation with NeuromorphIC vision

Ethan Elms, Mohsi Jawaid, Yasir Latif, Tat-Jun Chin

Dataset used in the paper "Towards Bridging the Space Domain Gap for Satellite Pose Estimation using Event Sensing" (link), for the purpose of satellite pose estimation with an event camera. Both events and ground truth camera poses were captured across the 20 …

au (code pays fourni par la source)

SEENIC: dataset for Spacecraft posE Estimation with NeuromorphIC vision

Ethan Elms, Mohsi Jawaid, Yasir Latif, Tat-Jun Chin

Dataset used in the paper "Towards Bridging the Space Domain Gap for Satellite Pose Estimation using Event Sensing" (arXiv, IEEE Xplore), for the purpose of satellite pose estimation with an event camera. Both events and ground truth camera poses were captured across …

au (code pays fourni par la source)

SEENIC: dataset for Spacecraft posE Estimation with NeuromorphIC vision

Ethan Elms, Mohsi Jawaid, Yasir Latif, Tat-Jun Chin

Dataset used in the paper "Towards Bridging the Space Domain Gap for Satellite Pose Estimation using Event Sensing" (arXiv, IEEE Xplore), for the purpose of satellite pose estimation with an event camera. Both events and ground truth camera poses were captured across …

au (code pays fourni par la source)

Towards Bridging the Space Domain Gap for Satellite Pose Estimation using Event Sensing

Mohsi Jawaid, Ethan Elms, Yasir Latif, Tat-Jun Chin

Deep models trained using synthetic data require domain adaptation to bridge the gap between the simulation and target environments. State-of-the-art domain adaptation methods often demand sufficient amounts of (unlabelled) data from the target domain. However, this need is difficult to fulfil when …