AI Search3D modeling for agricultural field inspection robot
Call Number: AIT Thesis no.CS-10-04 Material type:
SeriesSeries: Asian Institute of Technology. Thesis ; no. CS-10-04Publication details: Pathum Thani, Thailand : Asian Institute of Technology, 2010Description: 33 p. : illSubject(s): Online resources: Dissertation note: Thesis (M.Eng.) - Asian Institute of Technology, 2010 Summary: Through automated agricultural inspection, farmers can potentially achieve better produc-tivity and accurately predict yields and crop quality. The cheapest device for collecting richinformation about a crop is the video camera. This thesis focuses on the design, implemen-tation, and evaluation of algorithms for extracting information about a pineapple crop froma monocular webcam fixed to a mobile inspection platform. The process begins with fruitdetection and tracking in video sequence. I propose a 3D modeling algorithm that workswith the tracking history to generate a 3D point cloud for each fruit using structure-from-motion techniques in computer vision. The 3D modeling algorithm consists of two mainprocedures: 3D point cloud estimation and 3D fruit shape reconstruction. Once the 3D pointcloud for a fruit is obtained, the fruit shape reconstruction method estimates the shape andsize of the fruit using a robust ellipsoid estimation technique. A series of experiments showsthat the method produces a reasonably accurate 3D field map despite only partial and oc-cluded views of the fruit. The prototype is thus a promising step towards the realization ofautomated mobile in-field agricultural inspection systems.
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A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science, School of Engineering and Technology
Through automated agricultural inspection, farmers can potentially achieve better produc-tivity and accurately predict yields and crop quality. The cheapest device for collecting richinformation about a crop is the video camera. This thesis focuses on the design, implemen-tation, and evaluation of algorithms for extracting information about a pineapple crop froma monocular webcam fixed to a mobile inspection platform. The process begins with fruitdetection and tracking in video sequence. I propose a 3D modeling algorithm that workswith the tracking history to generate a 3D point cloud for each fruit using structure-from-motion techniques in computer vision. The 3D modeling algorithm consists of two mainprocedures: 3D point cloud estimation and 3D fruit shape reconstruction. Once the 3D pointcloud for a fruit is obtained, the fruit shape reconstruction method estimates the shape andsize of the fruit using a robust ellipsoid estimation technique. A series of experiments showsthat the method produces a reasonably accurate 3D field map despite only partial and oc-cluded views of the fruit. The prototype is thus a promising step towards the realization ofautomated mobile in-field agricultural inspection systems.
Thesis (M.Eng.) - Asian Institute of Technology, 2010
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