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Concept

Reconnaissance aérienne

Publications associées (25)

Improving Few-Shot Object Detection with Object Part Proposals

Devis Tuia, Marc Conrad Russwurm

Few-Shot Object Detection (FSOD) allows fast adaptation of an object detection model to new classes of objects using few examples per class. This has many applications, in particular in satellite and aerial observation, as it allows learning from experts w ...

The Institute of Electrical and Electronics Engineers, Inc2023

Stay close, but not too close: aerial image analysis reveals patterns of social distancing in seal colonies

Devis Tuia, Benjamin Alexander Kellenberger

Many species aggregate in dense colonies. Species-specific spatial patterns provide clues about how colonies are shaped by various (a)biotic factors, including predation, temperature regulation or disease transmission. Using aerial imagery, we examined the ...

2023

swissALPS: a Dataset for Imbalanced Land Cover Mapping in Alpine Regions

Valérie Zermatten

Our dataset consists of very high-resolution aerial images (50cm) and a digital elevation model (50cm) that covers approx. 2300 km2 of land above 2000m altitude in the southwestern part of Switzerland. Our land cover labels focus on alpine land cover that ...

IEEE DataPort2023

Cross-Modal Learning of Housing Quality in Amsterdam

Devis Tuia

In our research we test data and models for the recognition of housing quality in the city of Amsterdam from ground-level and aerial imagery. For ground-level images we compare Google StreetView (GSV) to Flickr images. Our results show that GSV predicts th ...

ACM2021

Self-Supervised Pretraining and Controlled Augmentation Improve Rare Wildlife Recognition in UAV Images

Devis Tuia, Benjamin Alexander Kellenberger

Automated animal censuses with aerial imagery are a vital ingredient towards wildlife conservation. Recent models are generally based on deep learning and thus require vast amounts of training data. Due to their scarcity and minuscule size, annotating anim ...

IEEE2021

Liveability from Above: Understanding Quality of Life with Overhead Imagery and Deep Neural Networks

Devis Tuia

Urban planners are increasingly interested in understanding what makes a neighbourhood pleasant and liveable. In this paper, we use the overhead perspective as a new way to describe and understand liveability of city neighborhoods. We predict building qual ...

IEEE2021

Towards Reliable Evaluation of Algorithms for Road Network Reconstruction from Aerial Images

Pascal Fua, Mateusz Kozinski, Leonardo Citraro

Existing connectivity-oriented performance measures rank road delineation algorithms inconsistently, which makes it difficult to decide which one is best for a given application. We show that these inconsistencies stem from design flaws that make the metri ...

2020

The Foldable Drone: A Morphing Quadrotor That Can Squeeze and Fly

Dario Floreano, Stefano Mintchev, Davide Scaramuzza

The recent advances in state estimation, perception, and navigation algorithms have significantly contributed to the ubiquitous use of quadrotors for inspection, mapping, and aerial imaging. To further increase the versatility of quadrotors, recent works i ...

2019

A Comparative Study of Collision Avoidance Algorithms for Unmanned Aerial Vehicles: Performance and Robustness to Noise

Denis Gillet, Alcherio Martinoli, Steven Adriaan Roelofsen

Over the past years, the field of small unmanned aerial vehicles has grown significantly and several applications have appeared, requiring always more autonomous flight. An important remaining challenge for fully autonomous unmanned aerial vehicles is coll ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

Sensitivity to Time Delays in VDM-Based Navigation

Jan Skaloud, Mehran Khaghani, Gabriel François Laupré

A recently proposed navigation methodology for aerial platforms based on the vehicle dynamic model (VDM) has shown promising results in terms of navigation autonomy. Its practical realization requires that control inputs are related to the same absolute ti ...

2019

Reconstructing Evolving Tree Structures in Time Lapse Sequences by Enforcing Time-Consistency

Pascal Fua, Engin Türetken, Raphael Sznitman, Agata Justyna Mosinska, Przemyslaw Rafal Glowacki, Jan Kybic

We propose a novel approach to reconstructing curvilinear tree structures evolving over time, such as road networks in 2D aerial images or neural structures in 3D microscopy stacks acquired in vivo. To enforce temporal consistency, we simultaneously proces ...

2017

Time synchronization of consumer cameras on Micro Aerial Vehicles

Jan Skaloud, Martin Rehak

This article discusses the problem of time registration between navigation and imaging components on Micro Aerial Vehicles (MAVs). Accurate mapping with MAVs is gaining importance in applications such as corridor mapping, road and pipeline inspections or m ...

Elsevier2017

Bundle adjustment with raw inertial observations

Jan Skaloud, Martin Rehak, Davide Antonio Cucci

t is well known that accurate aerial position and attitude control is beneficial for image orientation in airborne photogrammetry. The aerial control is traditionally obtained by Kalman filtering/smoothing inertial and GNSS observations prior to the bundle ...

2017

Accurate Optical Target Pose Determination For Applications In Aerial Photogrammetry

Davide Antonio Cucci

We propose a new design for an optical coded target based on concentric circles and a position and orientation determination algorithm optimized for high distances compared to the target size. If two ellipses are fitted on the edge pixels corresponding to ...

2016

Accurate Optical Target Pose Determination For Applications In Aerial Photogrammetry

Davide Antonio Cucci

Copernicus Gesellschaft Mbh2016

Combining Human Computing and Machine Learning to Make Sense of Big (Aerial) Data for Disaster Response

Devis Tuia, Stéphane Joost, Matthew Josef Parkan

Aerial imagery captured via unmanned aerial vehicles (UAVs) is playing an increasingly important role in disaster response. Unlike satellite imagery, aerial imagery can be captured and processed within hours rather than days. In addition, the spatial resol ...

Mary Ann Liebert, Inc2016

Multiscale Centerline Detection

Pascal Fua, Vincent Lepetit, Engin Türetken, Amos Sironi

Finding the centerline and estimating the radius of linear structures is a critical first step in many applications, ranging from road delineation in 2D aerial images to modeling blood vessels, lung bronchi, and dendritic arbors in 3D biomedical image stac ...

Institute of Electrical and Electronics Engineers2016

Coherence management in lithography printing systems

Hans Peter Herzig, Toralf Scharf, Johana Bernasconi

In proximity lithography, interference and diffraction effects arise when printing small features because of the proximity gap. Different techniques are used in order to control and take advantage of theses effects. In this paper, the focus is set on the M ...

Spie-Int Soc Optical Engineering2016

Applicability Of New Approaches Of Sensor Orientation To Micro Aerial Vehicles

Jan Skaloud, Martin Rehak

This study highlights the benefits of precise aerial position and attitude control in the context of mapping with Micro Aerial Vehicles (MAVs). Accurate mapping with MAVs is gaining importance in applications such as corridor mapping, road and pipeline ins ...

Copernicus Gesellschaft Mbh2016

Learning to Match Aerial Images with Deep Attentive Architectures

Pascal Fua, Eduard Trulls Fortuny

Image matching is a fundamental problem in Computer Vision. In the context of feature-based matching, SIFT and its variants have long excelled in a wide array of applications. However, for ultra-wide baselines, as in the case of aerial images captured unde ...

2016