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Davide Scaramuzza

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Publications associées (71)

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Are We Ready for Autonomous Drone Racing? The UZH-FPV Drone Racing Datase

Davide Scaramuzza, Titus Cieslewski

Despite impressive results in visual-inertial state estimation in recent years, high speed trajectories with six degree of freedom motion remain challenging for existing estimation algorithms. Aggressive trajectories feature large accelerations and rapid r ...

2019

Beyond Point Clouds: Fisher Information Field for Active Visual Localization

Davide Scaramuzza

For mobile robots to localize robustly, actively considering the perception requirement at the planning stage is essential. In this paper, we propose a novel representation for active visual localization. By formulating the Fisher information and sensor vi ...

2019

Event-based, Direct Camera Tracking from a Photometric 3D Map using Nonlinear Optimization

Davide Scaramuzza

Event cameras are novel bio-inspired vision sensors that output pixel-level intensity changes, called “events”, instead of traditional video images. These asynchronous sensors naturally respond to motion in the scene with very low latency (in the order of ...

2019

Deep Drone Racing: From Simulation to Reality with Domain Randomization

Davide Scaramuzza

Dynamically changing environments, unreliable state estimation, and operation under severe resource constraints are fundamental challenges for robotics, which still limit the deployment of small autonomous drones. We address these challenges in the context ...

2019

A Tutorial on Quantitative Trajectory Evaluation for Visual(-Inertial) Odometry

Davide Scaramuzza

In this tutorial, we provide principled methods to quantitatively evaluate the quality of an estimated trajectory from visual(-inertial) odometry (VO/VIO), which is the foundation of benchmarking the accuracy of different algorithms. First, we show how to ...

2019

Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing

Davide Scaramuzza

Autonomous micro aerial vehicles still struggle with fast and agile maneuvers, dynamic environments, imperfect sensing, and state estimation drift. Autonomous drone racing brings these challenges to the fore. Human pilots can fly a previously unseen track ...

2019

CED: Color Event Camera Dataset

Davide Scaramuzza

Event cameras are novel, bio-inspired visual sensors, whose pixels output asynchronous and independent times-tamped spikes at local intensity changes, called ‘events’. Event cameras offer advantages over conventional frame-based cameras in terms of latency ...

IEEE2019

Event-Based Motion Segmentation by Motion Compensation

Davide Scaramuzza

In contrast to traditional cameras, whose pixels have a common exposure time, event-based cameras are novel bio-inspired sensors whose pixels work independently and asynchronously output intensity changes (called "events"), with microsecond resolution. Sin ...

2019

Events-to-Video: Bringing Modern Computer Vision to Event Cameras

Davide Scaramuzza

Event cameras are novel sensors that report brightness changes in the form of asynchronous “events” instead of intensity frames. They have significant advantages over conventional cameras: high temporal resolution, high dynamic range, and no motion blur. S ...

2019

Focus Is All You Need: Loss Functions For Event-based Vision

Davide Scaramuzza

Event cameras are novel vision sensors that output pixel-level brightness changes (“events”) instead of traditional video frames. These asynchronous sensors offer several advantages over traditional cameras, such as, high temporal resolution, very high dyn ...

2019