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dc.contributor.advisorUsher, Colin
dc.contributor.advisorZhang, Fumin
dc.contributor.authorMuni, Aneri Dhirendra
dc.date.accessioned2018-08-20T19:11:00Z
dc.date.available2018-08-20T19:11:00Z
dc.date.created2018-05
dc.date.submittedMay 2018
dc.identifier.urihttp://hdl.handle.net/1853/60373
dc.description.abstractPoultry houses require daily monitoring to ensure animal health and proper house operation. One task involves observing the average growth rate of the house to adjust the daily feed. In addition to being labor intensive and time consuming, it is difficult for the farm owners to find consistent labor to fill these jobs. This project looks at the possibility of estimating the weight of a chicken based on the volume of the chicken as captured by a 3D model. We present a system capable of reconstructing dynamic scenes, i.e. chickens in a poultry house, by fusing together depth scans captured using a Microsoft Kinect. Like DynamicFusion, our approach involves discretizing the live depth frame into nodes and estimating individual 6D transformations before fusing them together to reconstruct scene geometry. This approach doesn’t use any prior model of template, making it applicable to a wide range of dynamic objects and scenes.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technology
dc.subject3D reconstruction
dc.subjectPoultry
dc.subjectAgriculture
dc.subjectChickens
dc.subjectVolumetric reconstruction
dc.subjectDynamicFusion
dc.subjectKinectFusion
dc.title3D Reconstruction of Live Chickens in Poultry Houses
dc.typeUndergraduate Research Option Thesis
dc.description.degreeUndergraduate
dc.contributor.departmentElectrical and Computer Engineering
thesis.degree.levelUndergraduate
dc.date.updated2018-08-20T19:11:00Z


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