Publications related to Trinocular Adaptive Window Size Disparity Estimation Algorithm and Its Real-Time Hardware

Related publications (40)

Individually optimized dynamic parallel transmit pulses for 3D high‐resolution SPACE imaging at 7T

Emilie Claire Sleight, Natalia Pato Montemayor, Bénédicte Marie Maréchal, Tom Hilbert, Thomas Yu, Tommaso Di Noto, Jocelyn Philippe, Lina Bacha

Purpose: Although clinical 7T MRI offers various advantages compared to lower field strengths, achieving spatially uniform flip angle distributions remains a challenge. Sampling Perfection with Application optimized Contrast using different flip angle Evol ...

Wiley2025

How Far Can a 1-Pixel Camera Go? Solving Vision Tasks Using Photoreceptors and Computationally Designed Visual Morphology

Jiawei Fu, Isabella Lucile Yu, Amir Roshan Zamir, Andrei Atanov, Rishubh Singh

A de facto standard approach in solving computer vision tasks is to use a common high-resolution camera and choose its placement on an agent based on human intuition. On the other hand, extremely simple and well-designed visual sensors found throughout nat ...

Springer Science and Business Media Deutschland GmbH2025

Electrical-Level Fault-Injection Attacks on FPGA-Based Systems

Dina Gamaleldin Ahmed Shawky Mahmoud

With the growth in the performance of general-purpose computing no longer following Moore's law and Dennard scaling, the use of hardware-specialized systems is common practice. Field-programmable gate arrays (FPGAs) are adopted in cloud and cyber-physical ...

EPFL2024

FlexiMem: Flexible Shared Virtual Memory for PCIe-attached FPGAs

Paolo Ienne, Canberk Sönmez, Mohamed Mahfouz Ahmed Kotb Shahawy, Cemalettin Cem Belentepe

Shared Virtual Memory (SVM) is a mechanism that allows host-side applications and FPGA accelerators to access the same virtual address space. It enables accelerating algorithms with unpredictable memory access patterns by making transparent pointer sharing ...

Institute of Electrical and Electronics Engineers Inc.2024

Towards quantum 3D imaging devices

Edoardo Charbon, Claudio Bruschini, Samuel Burri, Arin Can Ülkü, Paul Mos, Michael Alan Wayne

We introduce a new generation of 3D imaging devices based on quantum plenoptic imaging. Position-momentum entanglement and photon number correlations are exploited to provide a scan-free 3D image after post-processing of the collected light intensity signa ...

2021

Ex uno plures: how to construct high-speed movies of collapsing cavitation bubbles from a single image

Mohamed Farhat, Davide Bernardo Preso, Armand Baptiste Sieber

The time-resolved visualization of the dynamics of a cavitation bubble usually requires the use of expensive high-speed cameras, which often provide a limited spatial resolution. In the present study, we propose an alternative to these high-speed imaging t ...

Springer2023

Real-Time Localization for Closed-Loop Control of Assistive Furniture

Chuanfang Ning, Auke Ijspeert, Alexandre Massoud Alahi, George Adaimi, Anastasia Bolotnikova, Lixuan Tang

For people with limited mobility, navigating in cluttered indoor environment is challenging. In this work, we propose a mobile assistive furniture suite that is designed to ease the life of people with special needs in indoor movement. To enable intelligen ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Tracking and Relative Localization of Drone Swarms With a Vision-Based Headset

Dario Floreano, Fabrizio Schiano

We address the detection, tracking, and relative localization of the agents of a drone swarm from a human perspective using a headset equipped with a single camera and an Inertial Measurement Unit (IMU). We train and deploy a deep neural network detector o ...

2021

Towards Quantum 3D Imaging Devices

Edoardo Charbon, Claudio Bruschini, Samuel Burri, Arin Can Ülkü, Paul Mos, Michael Alan Wayne

We review the advancement of the research toward the design and implementation of quantum plenoptic cameras, radically novel 3D imaging devices that exploit both momentum–position entanglement and photon–number correlations to provide the typical refocusin ...

2021

State of the Art in Dense Monocular Non-Rigid 3D Reconstruction

Pascal Fua

3D reconstruction of deformable (or non-rigid) scenes from a set of monocular 2D image observations is a long-standing and actively researched area of computer vision and graphics. It is an ill-posed inverse problem, since-without additional prior assumpti ...

WILEY2023

Practical computational imaging by use of spatiotemporal light modulation: from simulations to applications in biological microscopy

François Thierry M Marelli

Optical microscopy is an essential tool for biologists, who are often faced with the need to overcome the spatial and temporal resolution limitations of their devices to capture finer details. As upgrading imaging hardware is expensive, computational metho ...

EPFL2023

Optimization Methods for Control: From Embedded Programmable Hardware to Data-Driven Process Optimization

Harsh Ambarishkumar Shukla

The research community has been making significant progress in hardware implementation, numerical computing and algorithm development for optimization-based control. However, there are two key challenges that still have to be overcome for optimization-base ...

EPFL2021

Beyond Cameras: Real-Time High-Resolution 3D and Panoramic MultiView Vision Systems with Their Applications

Bilal Demir

The cameras are invented by imitating the human visual system to capture the scene. The camera technologies have been substantially advanced in recent years. 108 MP resolution with 100x hybrid zoom has become standard features for smartphone flagships. In ...

EPFL2020

Towards learning-based denoising of light fields

Touradj Ebrahimi, Michela Testolina

In recent years, new emerging immersive imaging modalities, e.g. light fields, have been receiving growing attention, becoming increasingly widespread over the years. Light fields are often captured through multi-camera arrays or plenoptic cameras, with th ...

2023

A Visionary Look at the Security of Reconfigurable Cloud Computing

Francesco Regazzoni, Mirjana Stojilovic

Field-programmable gate arrays (FPGAs) have become critical components in many cloud computing platforms. These devices possess the fine-grained parallelism and specialization needed to accelerate applications ranging from machine learning to networking an ...

2023

Graph-based regularization of inverse problems in imaging

Mattia Rossi

As of today, the extension of the human visual capabilities to machines remains both a cornerstone and an open challenge in the attempt to develop intelligent systems. On the one hand, the development of more and more sophisticated imaging devices, capable ...

EPFL2020

Cross-resolution Face Recognition via Identity-Preserving Network and Knowledge Distillation

Touradj Ebrahimi, Yuhang Lu

Cross-resolution face recognition has become a challenging problem for modern deep face recognition systems. It aims at matching a low-resolution probe image with high-resolution gallery images registered in a database. Existing methods mainly leverage pri ...

2023

Learning stereo reconstruction with deep neural networks

Stepan Tulyakov

Stereo reconstruction is a problem of recovering a 3d structure of a scene from a pair of images of the scene, acquired from different viewpoints. It has been investigated for decades and many successful methods were developed. The main drawback of these ...

EPFL2020

Aliasing mitigation in optical microscopy of dynamic biological samples by use of temporally modulated color illumination and a standard RGB camera

Michael Stefan Daniel Liebling, Christian Jaques

Significance: Despite recent developments in microscopy, temporal aliasing can arise when imaging dynamic samples. Modern sampling frameworks, such as generalized sampling, mitigate aliasing but require measurement of temporally overlapping and potentially ...

SPIE Society of Photo-optical Instrumentation Engineers2020

Towards Real-World Super-Resolution using Deep Neural Networks

Ruofan Zhou

Image super-resolution reconstructs a higher-resolution image from the observed low-resolution image. In recent years, machine learning models have been widely employed and deep learning networks have achieved state-of-the-art super-resolution performance. ...

EPFL2020