Event-based vision for Robotics

Gallego Bonet, Guillermo (2019). Event-based vision for Robotics. In: "Research Seminar II at Escuela Politécnica Superior Universidad Autonoma de Madrid", 08 Abr 2019.

Description

Title: Event-based vision for Robotics
Author/s:
  • Gallego Bonet, Guillermo
Item Type: Presentation at Congress or Conference (Speech)
Event Title: Research Seminar II at Escuela Politécnica Superior Universidad Autonoma de Madrid
Event Dates: 08 Abr 2019
Title of Book: Research Seminar II at Escuela Politécnica Superior Universidad Autonoma de Madrid
Date: 8 April 2019
Subjects:
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (5MB) | Preview

Abstract

Event cameras, such as the Dynamic Vision Sensor (DVS), are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. They offer significant advantages over standard cameras, namely a very high dynamic range, no motion blur, and a latency in the order of microseconds. However, because the output is composed of a sequence of asynchronous events rather than actual intensity images, traditional vision algorithms cannot be applied, so that new algorithms that exploit the high temporal resolution and the asynchronous nature of the sensor are required. In this research seminar at the Escuela Politécnica Superior of the Universidad Autonoma de Madrid I provide a broad introduction to the topic. Then, I discuss two recent works on the use of event-based camera for motion estimation: event-based, 6-DOF camera tracking from photometric depth maps, and a unifying contrast maximization framework that allows us to solve multiple computer vision problems. Finally, I present an outlook of the future, learning-based approaches and the challenges that remain ahead of us.

More information

Item ID: 67281
DC Identifier: https://oa.upm.es/67281/
OAI Identifier: oai:oa.upm.es:67281
Deposited by: Dr Guillermo Gallego Bonet
Deposited on: 29 May 2021 10:12
Last Modified: 29 May 2021 10:12
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM