Sparsity-driven People Localization Algorithm: Evaluation in Crowded Scenes Environments

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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

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

Multi-object spectroscopic operations with the Sloan Digital Sky Survey V

Luzius Gregor Kronig, Ricardo Jorge Araùjo Pereira, Loïc Grossen

The Sloan Digital Sky Survey V (SDSS-V) is an all-sky spectroscopic survey of more than 6 million objects, designed to decode the history of the Milky Way, reveal the inner workings of stars, investigate the origin of solar systems, and track the growth of ...

SPIE-INT SOC OPTICAL ENGINEERING2020

Real-time camera pose estimation for sports fields

Stefano Savarè, Pascal Fua, Charles Dubout, Horesh Beny Ben Shitrit, Pablo Marquez Neila, Leonardo Citraro

Given an image sequence featuring a portion of a sports field filmed by a moving and uncalibrated camera, such as the one of the smartphones, our goal is to compute automatically in real time the focal length and extrinsic camera parameters for each image ...

2020

A deep learning framework for matching of SAR and optical imagery

Devis Tuia, Lloyd Haydn Hughes

SAR and optical imagery provide highly complementary information about observed scenes. A combined use of these two modalities is thus desirable in many data fusion scenarios. However, any data fusion task requires measurements to be accurately aligned. Wh ...

2020

On Variable Density Compressive Sampling

Pierre Vandergheynst, Yves Wiaux, Gilles Puy

We advocate an optimization procedure for variable density sampling in the context of compressed sensing. In this perspective, we introduce a minimization problem for the coherence between the sparsity and sensing bases, whose solution provides an optimize ...

IEEE Institute of Electrical and Electronics Engineers2011

Functional Performance Analysis and Optimization for the High-Frequency Magnetic Diagnostic System in ITER - II: Detailed Overview of the Analysis Method and of the Test Calculations

Jonathan Bryan Lister, Duccio Testa, Jean-Marc Moret, René Chavan, Matthieu Toussaint

The measurement performance of the baseline system design for the ITER high-frequency magnetic diagnostic system and attempts at its optimization have been performed using an innovative method based on the sparse representation of signals and the minimizat ...

American Nuclear Society2009