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Wolf_Thesis_FinalSubmission_v2__final format approved LW 12-12-2022.pdf (26.66 MB)
ETD Abstract Container
Abstract Header
Event Camera Applications for Driver-Assistive Technology
Author Info
Wolf, Abigail
ORCID® Identifier
http://orcid.org/0000-0002-2320-9945
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1671201967170428
Abstract Details
Year and Degree
2022, Master of Science in Computer Engineering, University of Dayton, Electrical and Computer Engineering.
Abstract
We propose an Event-Based Snow Removal algorithm called EBSnoR. We developed a technique to measure the dwell time of snowflakes on a pixel using event-based camera data, which is used to carry out a Neyman-Pearson hypothesis test to partition event stream into snowflake and background events. The effectiveness of the proposed EBSnoR was verified on a new dataset called UDayton22EBSnow, comprised of front-facing event-based camera in a car driving through snow with manually annotated bounding boxes around surrounding vehicles. Qualitatively, EBSnoR correctly identifies events corresponding to snowflakes; and quantitatively, EBSnoR-preprocessed event data improved the performance of event-based car detection algorithms.
Committee
Keigo Hirakawa (Committee Chair)
Vijayan Asari (Committee Member)
Bradley Ratliff (Committee Member)
Pages
45 p.
Subject Headings
Computer Engineering
Keywords
Event-based camera, snow removal, Neyman-Pearson hypothesis testing
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Refworks
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Citations
Wolf, A. (2022).
Event Camera Applications for Driver-Assistive Technology
[Master's thesis, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1671201967170428
APA Style (7th edition)
Wolf, Abigail.
Event Camera Applications for Driver-Assistive Technology.
2022. University of Dayton, Master's thesis.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1671201967170428.
MLA Style (8th edition)
Wolf, Abigail. "Event Camera Applications for Driver-Assistive Technology." Master's thesis, University of Dayton, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1671201967170428
Chicago Manual of Style (17th edition)
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Document number:
dayton1671201967170428
Download Count:
224
Copyright Info
© 2022, all rights reserved.
This open access ETD is published by University of Dayton and OhioLINK.