Lifetime Estimation Of Events From Dynamic Vision Sensors

• doi: 10.1109/ICRA.2015.7139876
• title: Lifetime estimation of events from Dynamic Vision Sensors
• publisher: IEEE
• isbn: 978-1-4799-6921-0
• issn: 1050-4729
• rank: 2870
• access_type: LOCKED
• content_type: Conferences
• abstract: We propose an algorithm to estimate the “lifetime” of events from retinal cameras, such as a Dynamic Vision Sensor (DVS). Unlike standard CMOS cameras, a DVS only transmits pixel-level brightness changes (“events”) at the time they occur with micro-second resolution. Due to its low latency and sparse output, this sensor is very promising for high-speed mobile robotic applications. We develop an algorithm that augments each event with its lifetime, which is computed from the event's velocity on the image plane. The generated stream of augmented events gives a continuous representation of events in time, hence enabling the design of new algorithms that outperform those based on the accumulation of events over fixed, artificially-chosen time intervals. A direct application of this augmented stream is the construction of sharp gradient (edge-like) images at any time instant. We successfully demonstrate our method in different scenarios, including high-speed quadrotor flips, and compare it to standard visualization methods.
• article_number: 7139876
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7139876
• html_url: https://ieeexplore.ieee.org/document/7139876/
• abstract_url: https://ieeexplore.ieee.org/document/7139876/
• publication_title: 2015 IEEE International Conference on Robotics and Automation (ICRA)
• conference_location: Seattle, WA, USA
• conference_dates: 26-30 May 2015
• publication_number: 7128761
• is_number: 7138973
• publication_year: 2015
• publication_date: 26-30 May 2015
• start_page: 4874
• end_page: 4881
• citing_paper_count: 79
• citing_patent_count: 9
• download_count: 1434
• insert_date: 20150702
• index_terms:
  • ieee_terms:
    • Voltage control
    • Sensors
    • Cameras
    • Standards
    • Noise
    • Brightness
    • Heuristic algorithms
  • dynamic_index_terms:
    • Vision Sensors
    • Dynamic Vision Sensor
    • Event Camera
    • Image Plane
    • Fundus Photography
    • Fundus Camera
    • Retinal Photographs
    • Low Latency
    • Robotic Applications
    • Representation Of Events
    • Brightness Changes
    • Standard Camera
    • Event Stream
    • Low Resolution
    • First Approximation
    • First-order Approximation
    • Past Events
    • Standard Algorithm
    • Constant Velocity
    • Pixel Resolution
    • Temporal Window
    • Optical Flow
    • Current Events
    • Window Function
    • Window Frames
    • Image Sharpness
    • Naive Method
    • Simultaneous Localization And Mapping
    • Motion Blur
    • Iterative Closest Point
    • Fixed Time Interval
    • Sensor Noise
    • Neighboring Pixels
    • Neighborhood Pixels
    • Scene Depth
    • Noise Suppression
    • Active Noise Control
    • Noise-canceling
• isbn_formats:
  • format: DVD ISBN, value: 978-1-4799-6921-0, isbnType: New-2005
  • format: Electronic ISBN, value: 978-1-4799-6923-4, isbnType: New-2005
• authors:
  • Author Name: Elias Mueggler
    Affiliation: Robotics and Perception Group, University of Zurich, Switzerland
    Author URL: https://ieeexplore.ieee.org/author/38541108800
    ID: 38541108800
    Order: 1
    Author Affiliations:
    • Robotics and Perception Group, University of Zurich, Switzerland
  • Author Name: Christian Forster
    Affiliation: Robotics and Perception Group, University of Zurich, Switzerland
    Author URL: https://ieeexplore.ieee.org/author/37710549400
    ID: 37710549400
    Order: 2
    Author Affiliations:
    • Robotics and Perception Group, University of Zurich, Switzerland
  • Author Name: Nathan Baumli
    Affiliation: Robotics and Perception Group, University of Zurich, Switzerland
    Author URL: https://ieeexplore.ieee.org/author/37085563732
    ID: 37085563732
    Order: 3
    Author Affiliations:
    • Robotics and Perception Group, University of Zurich, Switzerland
  • Author Name: Guillermo Gallego
    Affiliation: Robotics and Perception Group, University of Zurich, Switzerland
    Author URL: https://ieeexplore.ieee.org/author/37426725000
    ID: 37426725000
    Order: 4
    Author Affiliations:
    • Robotics and Perception Group, University of Zurich, Switzerland
  • Author Name: Davide Scaramuzza
    Affiliation: Robotics and Perception Group, University of Zurich, Switzerland
    Author URL: https://ieeexplore.ieee.org/author/37397688400
    ID: 37397688400
    Order: 5
    Author Affiliations:
    • Robotics and Perception Group, University of Zurich, Switzerland

Image Sensor

• sensor_type: CMOS
• resolution: 128x128
• dynamic_range: 120dB
• pixel_size: unknown
• dark_current: unknown

Optical Data

• focal_length: unknown
• aperture: unknown
• field_of_view: unknown
• distortion: unknown

Performance Metrics

• frame_rate: unknown
• signal_to_noise_ratio: unknown
• sensitivity: unknown
• shutter_speed: unknown
• power_consumption: unknown
• noise: unknown

Applications & Benefits

• cell_imaging: unknown
• benefits: Reduced bandwidth requirements, low latency, high dynamic range, and suitability for high-speed mobile robotic applications.

Supporting Organizations

• supported_by: Swiss National Science Foundation, National Centre of Competence in Research Robotics, Google

Manuscript Details

• publication_date: 26-30 May 2015

Relevancy Score

• score: 8
• missing_fields:
  • pixel_size
  • dark_current
  • focal_length
  • aperture
  • field_of_view
  • distortion
  • frame_rate
  • signal_to_noise_ratio
  • sensitivity
  • shutter_speed
  • power_consumption
  • noise
  • cell_imaging

Processed JSON Filename

request_04faa08b-436c-4899-8f91-47761294ff54-lifetime_estimation_of_events_from_dynamic_vision_sensors.json