Staff View
Stereo vision-based vehicular proximity estimation

Descriptive

TitleInfo
Title
Stereo vision-based vehicular proximity estimation
Name (type = personal)
NamePart (type = family)
Krishna
NamePart (type = given)
Arjun
NamePart (type = date)
1991-
DisplayForm
Arjun Krishna
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Lindqvist
NamePart (type = given)
Janne
DisplayForm
Janne Lindqvist
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Sarwate
NamePart (type = given)
Anand
DisplayForm
Anand Sarwate
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Zhang
NamePart (type = given)
Yanyong
DisplayForm
Yanyong Zhang
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2014
DateOther (qualifier = exact); (type = degree)
2014-10
CopyrightDate (encoding = w3cdtf)
2014
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
This thesis describes an innovative and cost effective method to develop a low-cost following distance logging algorithm for volunteer participants which will allow quantitative research in driving behavior. Sparse stereo depth estimation methods along with a license plate localization algorithm has been used in order to achieve this. The depth is estimated by processing the video feeds from the stereo camera setup mounted inside a car looking out of the front window. License plate localization is used as a means to localize the position of the car within the image. Depth is estimated from the disparity, which is calculated using the rectified images of the frames from both the video streams.
Subject (authority = RUETD)
Topic
Electrical and Computer Engineering
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_5899
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (vii, 45 p. : ill.)
Note (type = degree)
M.S.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Motor vehicle driving
Subject (authority = ETD-LCSH)
Topic
Image processing
Subject (authority = ETD-LCSH)
Topic
Depth perception
Note (type = statement of responsibility)
by Arjun Krishna
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T3BZ64HH
Genre (authority = ExL-Esploro)
ETD graduate
Back to the top

Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Krishna
GivenName
Arjun
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2014-09-24 20:44:24
AssociatedEntity
Name
Arjun Krishna
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
Back to the top

Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
Back to the top
Version 8.3.13
Rutgers University Libraries - Copyright ©2021