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Mohammed's Dissertation __ final format approved LW 12-9-19.pdf (7.92 MB)
ETD Abstract Container
Abstract Header
Optical Flow for Event Detection Camera
Author Info
Almatrafi, Mohammed Mutlaq
ORCID® Identifier
http://orcid.org/0000-0002-6701-4250
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1576188397203882
Abstract Details
Year and Degree
2019, Doctor of Philosophy (Ph.D.), University of Dayton, Electrical and Computer Engineering.
Abstract
Optical flow (OF) which refers to the task of determining the apparent motion of objects in the scene has been a topic of core interest in commuter vision for the past three decades. Optical flow methods of conventional camera struggle in the presence of large motion and occlusion due to slow frame rates. Optical flow of dynamic vision sensor (DVS) has gained attention recently as a way to overcome these shortcomings. DVS known also as event detection camera emerged recently as an alternative to a conventional camera by replacing a fixed analog-to-digital (A/D) converter with a floating asynchronous circuit. Rather than reporting a pixel intensity at a fixed time interval, the event detection cameras report only the significant changes (i.e. above threshold) to the pixel intensity (the “events”) and the time that such event occurs. Such circuit significantly reduces the communication bandwidth of the camera, enabling the operation at equivalent of roughly 80,000 frames per second. In addition, the floating A/D converter may adapt to extremely high dynamic range, making it suitable for applications in automotives and scientific instruments. However, the sparsity of the output data renders existing image processing and computer vision methods useless. For example, the “brightness constancy constraint” that is at the heart of optical flow does not apply to the edge-like features that event detection cameras output, and the very notion of “frames” is absent in the asynchronous outputs. In this work, we consider a new sensor called DAViS that combines the conventional active pixel sensor (APS) and DVS circuitries, yielding a conventional intensity image frames as well as the events. We propose three novel optical flow methods: First, We propose a novel optical flow method designed specifically for a DAViS camera that leverages the high spatial fidelity of intensity image frames and the high temporal resolution of events generated by DVS. Hence, the proposed DAViS-OF method yields reliable motion vector estimates while overcoming the fast motion and occlusion problems. Secondly, we develop a novel DVS optical flow method using the 2D distance transform---computed from the detected events---as a proxy for object texture. Treating multiple 2D distance transforms collectively as a ``distance surface'' improves optical flow significantly over working directly with the sparse events generated by the DVS camera. Finally, we introduce a new DVS-based method that extend the notion of 2D distance transform into 3D distance transform by incorporating the temporal information, resulting in reliable optical flow estimate. Real sensor experiments verify the accuracy and robustness of proposed methods to reliably recover the true two dimensional pixel motion, not limited to the ``normal flow.''
Committee
Keigo Hirakawa (Committee Chair)
Pages
77 p.
Subject Headings
Electrical Engineering
;
Engineering
Keywords
Optical Flow
;
Dynamic Vision Sensor
;
DVS
;
Event Camera
;
Motion Estimation
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Citations
Almatrafi, M. M. (2019).
Optical Flow for Event Detection Camera
[Doctoral dissertation, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1576188397203882
APA Style (7th edition)
Almatrafi, Mohammed.
Optical Flow for Event Detection Camera .
2019. University of Dayton, Doctoral dissertation.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1576188397203882.
MLA Style (8th edition)
Almatrafi, Mohammed. "Optical Flow for Event Detection Camera ." Doctoral dissertation, University of Dayton, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1576188397203882
Chicago Manual of Style (17th edition)
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Document number:
dayton1576188397203882
Download Count:
208
Copyright Info
© 2019, all rights reserved.
This open access ETD is published by University of Dayton and OhioLINK.
Release 3.2.12