Simultaneous optical flow and segmentation (SOFAS) using dynamic vision sensor

Timo Stoffregen, Lindsay Kleeman

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

11 Citations (Scopus)


We present an algorithm (SOFAS) to estimate the optical flow of events generated by a dynamic vision sensor (DVS). Where traditional cameras produce frames at a fixed rate, DVSs produce asynchronous events in response to intensity changes with a high temporal resolution. Our algorithm uses the fact that events are generated by edges in the scene to not only estimate the optical flow but also to simultaneously segment the image into objects which are travelling at the same velocity. This way it is able to avoid the aperture problem which affects other implementations such as Lucas- Kanade. Finally, we show that SOFAS produces more accurate results than traditional optic flow algorithms.

Original languageEnglish
Title of host publicationACRA 2017 - Australasian Conference on Robotics and Automation 2017
EditorsSarath Kodagoda, Teresa Vidal Calleja, Alen Alempijevic
Place of PublicationSydney Australia
PublisherAustralian Robotics and Automation Association (ARAA)
Number of pages10
ISBN (Electronic)9780980740486
Publication statusPublished - 2017
EventAustralasian Conference on Robotics and Automation 2017 - University of Technology Sydney, Sydney, Australia
Duration: 11 Dec 201713 Dec 2017


ConferenceAustralasian Conference on Robotics and Automation 2017
Abbreviated titleACRA 2017
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