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dc.contributor.authorMohamed, Aen
dc.contributor.authorCulverhouse, PFen
dc.contributor.authorCangelosi, Aen
dc.contributor.authorYang, Cen
dc.date.accessioned2018-11-30T15:08:09Z
dc.date.available2018-11-30T15:08:09Z
dc.identifier.issn2169-3536en
dc.identifier.urihttp://hdl.handle.net/10026.1/12964
dc.description.abstract

OAPA A depth estimation algorithm based on vergence vision using a mechanical joint attached to two cameras is proposed. A Gaussian pyramid template-matching approach is used to align the view of the slave camera to the fixation point of the master camera. The master camera uses an object detection algorithm to find the target’s centroid and centers it relative to the image coordinates. Then, vergence movement of the slave camera is performed using a pyramid normalized cross-correlation algorithm. Simple geometric triangulation is employed to compute the depth of that target. This proposed method was implemented using an active binocular vision platform with five degrees of freedom where four degrees of freedom to control the pan and tilt independently, and one degree of freedom to control the baseline which is the distance between the camera. This system was designed for implementation in agriculture harvesting applications. Analysis of field trial results indicates a worst-case precision of a target tomatoes’ depth to be ±1.32 cm at a depth of 85 cm.

en
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.titleDepth Estimation Based on Pyramid Normalized Cross-correlation Algorithm for Vergence Controlen
dc.typeJournal Article
plymouth.journalIEEE Accessen
dc.identifier.doi10.1109/ACCESS.2018.2877721en
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/00 Groups by role
plymouth.organisational-group/Plymouth/00 Groups by role/Academics
plymouth.organisational-group/Plymouth/00 Groups by role/Professional Services staff
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering/School of Computing, Electronics and Mathematics
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics
plymouth.organisational-group/Plymouth/Research Groups
plymouth.organisational-group/Plymouth/Research Groups/Institute of Health and Community
plymouth.organisational-group/Plymouth/Research Groups/Marine Institute
dcterms.dateAccepted2018-10-10en
dc.rights.embargodate2019-01-11en
dc.identifier.eissn2169-3536en
dc.rights.embargoperiodNot knownen
rioxxterms.versionofrecord10.1109/ACCESS.2018.2877721en
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by-sa/4.0/en
rioxxterms.typeJournal Article/Reviewen


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