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dc.contributor.authorHrzich, Joe
dc.date.accessioned2024-05-16T21:41:08Z
dc.date.available2024-05-16T21:41:08Z
dc.date.issued2024-04-23
dc.identifier.citationHrzich, Joe. An All-In-One, Low-Cost Photogrammetry Rig for 3D Plant Modelling and Phenotyping; A thesis/proposal submitted to the Faculty of Graduate Studies of The University of Winnipeg in partial fulfillment of the requirements of the degree of Master[] of Science, Department of Applied Computer Science, The University of Winnipeg. Winnipeg, Manitoba, Canada: University of Winnipeg, 2024. DOI: 10.36939/ir.202405161638.en_US
dc.identifier.urihttps://hdl.handle.net/10680/2141
dc.description.abstractPhotogrammetry, the science of generating 3D models of objects from photographs, offers a comprehensive method for acquiring, studying, and analyzing detailed information about the structure of objects. Utilizing the cost-effective Structure from Motion (SfM) technique, it is possible to generate 3D models from numerous 2D images taken from various angles. Point clouds represent a standard format for 3D data generated by depth sensors such as LIDARs and RGB-D cameras. Despite their utility, high-quality 3D scanners, costing upwards of $70,000, remain relatively expensive for many researchers and practitioners within the agricultural sector. In response, we have developed a low-cost, close-range photogrammetry rig, priced at $2,600, to support agronomists, plant scientists, and breeders. This work outlines the development of our device, which integrates a multi-camera system featuring the Arducam 64MP Autofocus Quad-Camera Kit, a rotary table from Ortery, and a Raspberry Pi for comprehensive control and processing. Our scanner efficiently captures detailed plant 3D data, offering a valuable tool for non-destructive, automatic, and robust 3D phenotyping. It is possible to use our device across various applications, including growth monitoring and the extraction of plant traits. Specifically, we have leveraged the device to measure the canopy volume of different wheat genotypes by computing the convex hull from the 3D data. Furthermore, through our photogrammetry rig, we have developed a high-throughput, quantitative trait index for wheat to identify distinct planophile and erectophile canopy architectures.en_US
dc.description.sponsorshipMitacsen_US
dc.language.isoenen_US
dc.publisherUniversity of Winnipegen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectPhotogrammetryen_US
dc.subject3D phenomicsen_US
dc.subjectCrop modellingen_US
dc.subjectPlant growthen_US
dc.subjectLow-costen_US
dc.subjectPoint clouden_US
dc.subjectStructure from Motion (SfM)en_US
dc.titleAn All-In-One, Low-Cost Photogrammetry Rig for 3D Plant Modelling and Phenotypingen_US
dc.typeThesisen_US
dc.description.degreeMaster of Science in Applied Computer Scienceen_US
dc.publisher.grantorUniversity of Winnipegen_US
dc.identifier.doi10.36939/ir.202405161638en_US
thesis.degree.disciplineApplied Computer Science
thesis.degree.levelmasters
thesis.degree.nameMaster of Science in Applied Computer Science
thesis.degree.grantorUniversity of Winnipeg


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