SiROP
Login   
Language
  • English
    • English
    • German
Home
Menu
  • Login
  • Register
  • Search Opportunity
  • Search Organization
  • Create project alert
Information
  • About SiROP
  • Team
  • Network
  • Partners
  • Imprint
  • Terms & conditions
Register now After registration you will be able to apply for this opportunity online.
This opportunity is not published. No applications will be accepted.

Learning an Event Camera

Event cameras such as the Dynamic Vision Sensor (DVS) are recent sensors with a lot of potential for high-speed and high dynamic range robotic applications. They have been successfully applied in many applications, such as high speed video and high speed visual odometry. In spite of this success, the exact operating principle of event cameras, that is, how events are generated from a given visual signal and how noise is generated, is not well understood. In his work we want to explore new techniques for modelling the generation of events in an event camera, which would have wide implications for existing techniques. Applicants should have a background in C++ programming and low-level vision. In addition, familiarity with learning frameworks such as pytorch or tensorflow are required.

Keywords: Event Camera, DVS, DAVIS, Learning, Asynchronous, low-latency, high-dynamic-range, modeling, computer vision, event camera

  • Event cameras such as the Dynamic Vision Sensor (DVS) are recent sensors with a lot of potential for high-speed and high dynamic range robotic applications. They have been successfully applied in many applications, such as high speed video and high speed visual odometry. In spite of this success, the exact operating principle of event cameras, that is, how events are generated from a given visual signal and how noise is generated, is not well understood. In his work we want to explore new techniques for modelling the generation of events in an event camera, which would have wide implications for existing techniques. Applicants should have a background in C++ programming and low-level vision. In addition, familiarity with learning frameworks such as pytorch or tensorflow are required.

    Event cameras such as the Dynamic Vision Sensor (DVS) are recent sensors with a lot of potential for high-speed and high dynamic range robotic applications. They have been successfully applied in many applications, such as high speed video and high speed visual odometry. In spite of this success, the exact operating principle of event cameras, that is, how events are generated from a given visual signal and how noise is generated, is not well understood. In his work we want to explore new techniques for modelling the generation of events in an event camera, which would have wide implications for existing techniques. Applicants should have a background in C++ programming and low-level vision. In addition, familiarity with learning frameworks such as pytorch or tensorflow are required.

  • The goal of this project is to explore new techniques for modelling an event camera.

    The goal of this project is to explore new techniques for modelling an event camera.

  • Daniel Gehrig (dgehrig (at) ifi (dot) uzh (dot) ch), Mathias Gehrig (mgehrig (at) ifi (dot) uzh (dot) ch)

    Daniel Gehrig (dgehrig (at) ifi (dot) uzh (dot) ch), Mathias Gehrig (mgehrig (at) ifi (dot) uzh (dot) ch)

Calendar

Earliest start2020-05-15
Latest end2022-03-17

Location

Robotics and Perception (UZH)

Labels

Semester Project

Internship

Master Thesis

Topics

  • Information, Computing and Communication Sciences
SiROP PARTNER INSTITUTIONS