Searched for: subject%3A%22optical%255C%2Bflow%22
(1 - 20 of 38)

Pages

document
Paredes-Vallés, Federico (author)
In the ever-evolving landscape of robotics, the quest for advanced synthetic machines that seamlessly integrate with human lives and society becomes increasingly paramount. At the heart of this pursuit lies the intrinsic need for these machines to perceive, understand, and navigate their surroundings autonomously. Among the senses, vision...
doctoral thesis 2023
document
WANG, NIAN RU (author)
This thesis presents LightLetter, a system that is designed for recognizing fingertip air-writing of both numbers and letters. This provides a cost-effective and privacy-conscious method for interacting with public devices, such as touchscreens. The current iteration of LightLetter allows for the input of letters and numbers to public devices...
master thesis 2023
document
Elbertse, Mitchel (author)
Autonomous vehicles are becoming increasingly prevalent in society, but the transition from active driver to passive passenger is known to increase the risk and severity of motion sickness. Motion anticipation is a critical factor in this difference, and visual information is known to be a major contributor to motion anticipation. However, the...
master thesis 2023
document
Gielisse, A.S. (author)
Most recent works on optical flow use convex upsampling as the last step to obtain high-resolution flow. In this work, we show and discuss several issues and limitations of this currently widely adopted convex upsampling approach. We propose a series of changes, inspired by the observation that convex upsampling as currently implemented performs...
master thesis 2023
document
Shi, Rui (author), Wüthrich, D. (author), Chanson, Hubert (author)
Transient motion, turbulence and bubble dynamics make any velocity quantification extremely difficult in unsteady gas–liquid flows. In the present study, novel Eulerian and Lagrangian techniques of velocimetry were developed, using both intrusive and non-intrusive measurements. The selected unsteady gas–liquid flow was a breaking bore,...
journal article 2023
document
de Alvear Cardenas, Jose Ignacio (author)
Despite the camera being ubiquitous to unmanned aerial vehicles (UAVs), it has not been used for fault detection and diagnosis (FDD) due to the nonexistence of UAV multi-sensor datasets that include actuator failure scenarios. This thesis proposes a knowledge-based FDD framework based on a lightweight Long-Short Term Memory network that fuses...
master thesis 2022
document
Shetty, Siddhy Ganesh (author)
With the advancement in technology, Unmanned Aerial Vehicles (UAVs) have been able to safely maneuver in risky environments. During landing, the UAV should be able to slow down while not affecting its physical design. Currently, multiple sensors are being used to increase the accuracy while landing which might weigh down some of the smaller UAVs...
master thesis 2022
document
Bouwmeester, Rik (author)
Nano quadcopters are small, agile, and cheap platforms well suited for deployment in narrow, cluttered environments. Due to their limited payload, nano quadcopters are highly constrained in processing power, rendering conventional vision-based methods for autonomous navigation incompatible. Recent machine learning developments promise high...
master thesis 2022
document
Eggers, Yvonne (author)
Event cameras and spiking neural networks (SNNs) allow for a highly bio-inspired, low-latency and power efficient implementation of optic flow estimation. Just recently, a hierarchical SNN was proposed in which motion selectivity is learned from raw event data in an unsupervised manner using spike-timing-dependent plasticity (STDP). However,...
master thesis 2022
document
Tran, Tommy (author)
Semantic segmentation methods have been developed and applied to single images for object segmentation. However, for robotic applications such as high-speed agile Micro Air Vehicles (MAVs) in Autonomous Drone Racing (ADR), it is more interesting to consider temporal information as video sequences are correlated over time. In this work, we...
master thesis 2022
document
Arosquipa Nina, Yvan (author), Shi, Rui (author), Wüthrich, D. (author), Chanson, Hubert (author)
Self-aerated free-surface flow studies have a more recent history compared to classical fluid dynamics. Traditional velocimetry techniques are adversely affected by the presence of gas–liquid interfaces. In the present study, detailed air-water flow measurements were performed in a highly turbulent free-surface flow, and three velocimetry...
journal article 2022
document
de Jong, D.B. (author), Paredes-Vallés, Federico (author), de Croon, G.C.H.E. (author)
End-to-end trained convolutional neural networks have led to a breakthrough in optical flow estimation. The most recent advances focus on improving the optical flow estimation by improving the architecture and setting a new benchmark on the publicly available MPI-Sintel dataset. Instead, in this article, we investigate how deep neural...
journal article 2022
document
Dong, Xichao (author), Zhao, Zewei (author), Wang, Yupei (author), Wang, J. (author), Hu, Cheng (author)
Nowadays deep learning-based weather radar echo extrapolation methods have competently improved nowcasting quality. Current pure convolutional or convolutional recurrent neural network-based extrapolation pipelines inherently struggle in capturing both global and local spatiotemporal interactions simultaneously, thereby limiting nowcasting...
journal article 2022
document
Vroon, Erik (author)
Drones need to be able to detect and localize each other if they are to collaborate in multi-robot teams or swarms. Typically, computer vision methods based on visual appearance are investigated to this end. In contrast, in this work, a method based on dense optical flow (OF) is developed that detects dynamic objects. This is achieved by...
master thesis 2021
document
Addaguduri Aditya, Aditya (author)
This project aims to explore the possibility of monitoring the vitals of the neonate remotely and without placing any sensors or electrodes on the subjects body using Thermal Imaging.
master thesis 2021
document
Dinaux, Raoul (author)
Micro Air Vehicles (MAVs) are able to support humans in dangerous operations, such as search and rescue operations at night on unknown terrain. These scenes require a great amount of autonomy from the MAV, as they are often radio and GPS-denied. As MAVs have limited computational resources and energy storage, onboard navigation tasks have to be...
master thesis 2021
document
Tomy, Abhishek (author)
A human driver can gauge the intention and signals given by other road users indicative of their future behaviour. The intentions and signals are identified by looking at the cues originating from vulnerable road users or their surroundings (hand signals, head orientation, posture, traffic signals, distance to curb, etc.). Taking all these cues...
master thesis 2020
document
de Jong, David (author)
End-to-end trained Convolutional Neural Networks have led to a breakthrough in optical flow estimation. The most recent advances focus on improving the optical flow estimation by improving the architecture and setting a new benchmark on the publicly available MPI-Sintel dataset. Instead, in this article, we investigate how deep neural networks...
master thesis 2020
document
Hagenaars, Jesse (author)
Flying insects are capable of autonomous vision-based navigation in cluttered environments, reliably avoiding objects through fast and agile manoeuvres. Meanwhile, insect-scale micro air vehicles still lag far behind their biological counterparts, displaying inferior performance at a fraction of the energy efficiency. In light of this, it is in...
master thesis 2020
document
Bosboom, J. (author)
This thesis investigates the behaviour of the often used point-wise skill score, the MSESSini a.k.a. BSS, and develops new error metrics that, as opposed to point-wise metrics, take the spatial structure of morphological patterns into account. The...
doctoral thesis 2020
Searched for: subject%3A%22optical%255C%2Bflow%22
(1 - 20 of 38)

Pages