Adam James Scholefield

Biography

Adam Scholefield received the MEng in Electric and Electronic Engineering from Imperial College London in 2007.After a brief interuption of studies to compete in the Olympic Games, he received the PhD from the Communications and Signal Processing Group of Imperial College in 2013. His thesis was titled “Quadtree Structured Approximation Algorithms” and focused on image approximation algorithms with applications in image restoration.Since June 2014, he has served as a postdoctoral researcher in the Audiovisual Communications Laboratory (LCAV) at EPFL.

Official source

https://people.epfl.ch/adam.scholefield

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In event-based sensing, many sensors independently and asynchronously emit events when there is a change in their input. Event-based sensing can present significant improvements in power efficiency when compared to traditional sampling, because (1) the output is a stream of events where the important information lies in the timing of the events, and (2) the sensor can easily be controlled to output information only when interesting activity occurs at the input. Moreover, event-based sampling can often provide better resolution than standard uniform sampling. Not only does this occur because individual event-based sensors have higher temporal resolution (Rebecq et al., 2021) it also occurs because the asynchrony of events within a sensor and therefore across sensors allows for less redundant and more informative encoding. We would like to explain how such curious results come about. To do so, we use ideal time encoding machines as a proxy for event-based sensors. We explore time encoding of signals with low rank structure, and apply the resulting theory to video. We then see how the asynchronous firing across time encoding machines can couple spatial sampling density with temporal resolution, leading to better reconstruction, whereas, in frame-based video, temporal resolution depends solely on the frame-rate and spatial resolution solely on the pixel grid used.

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Blind as a Bat: Audible Echolocation on Small Robots

Frederike Dümbgen, Adrien Guillaume Olivier Hoffet, Mihailo Kolundzija, Adam James Scholefield, Martin Vetterli

For safe and efficient operation, mobile robots need to perceive their environment, and in particular, perform tasks such as obstacle detection, localization, and mapping. Although robots are often equipped with microphones and speakers, the audio modality is rarely used for these tasks. Compared to the localization of sound sources, for which many practical solutions exist, algorithms for active echolocation are less developed and often rely on hardware requirements that are out of reach for small robots. We propose an end-to-end pipeline for sound-based localization and mapping that is targeted at, but not limited to, robots equipped with only simple buzzers and low-end microphones. The method is model-based, runs in real time, and requires no prior calibration or training. We successfully test the algorithm on the e-puck robot with its integrated audio hardware, and on the Crazyflie drone, for which we design a reproducible audio extension deck. We achieve centimeter-level wall localization on both platforms when the robots are static during the measurement process. Even in the more challenging setting of a flying drone, we can successfully localize walls, which we demonstrate in a proof-of-concept multi-wall localization and mapping demo.

2022

Lippmann Photography: A Signal Processing Perspective

Gilles Baechler, Arnaud Latty, Michalina Wanda Pacholska, Adam James Scholefield, Martin Vetterli

Lippmann (or interferential) photography is the first and only analog photography method that can capture the full color spectrum of a scene in a single take. This technique, invented more than a hundred years ago, records the colors by creating interference patterns inside the photosensitive plate. Lippmann photography provides a great opportunity to demonstrate several fundamental concepts in signal processing. Conversely, a signal processing perspective enables us to shed new light on the technique. In our previous work (G. Baechler et al., 2021), we analyzed the spectra of historical Lippmann plates using our own mathematical model. In this paper, we provide the derivation of this model and validate it experimentally. We highlight new behaviors whose explanations were ignored by physicists to date. In particular, we show that the spectra generated by Lippmann plates are in fact distorted versions of the original spectra. We also show that these distortions are influenced by the thickness of the plate and the reflection coefficient of the reflective medium used in the capture of the photographs. We verify our model with extensive experiments on our own Lippmann photographs.

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022