Inertially Constrained Ruled Surfaces for Visual Odometry

dc.contributor.advisorAloimonos, Yiannisen_US
dc.contributor.authorZhu, Chenqien_US
dc.contributor.departmentComputer Scienceen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2025-01-29T06:42:09Z
dc.date.available2025-01-29T06:42:09Z
dc.date.issued2024en_US
dc.description.abstractIn computer vision, camera egomotion is typically solved with visual odometry techniques that relies on feature extraction from a sequence of images and computation of the optical flow. This, however, often requires a point-to-point correspondence between two consecutive frames which can often be costly to compute and its varying accuracy greatly affects the quality of estimated motion. Attempts have been made to bypass the difficulties originated from the correspondence problem by adopting line features and fusing other sensors (event camera, IMU), many of which still heavily rely on feature detectors. If the camera observes a straight line as it moves, the image of such line is sweeping a surface, this is a ruled surface and analyzing its shapes gives information about the egomotion. This research presents a novel algorithm to estimate 3D camera egomotion from scenes represented by ruled surfaces. Constraining the egomotion with inertia measurements from an onboard IMU sensor, the dimensionality of the solution space is greatly reduced.en_US
dc.identifierhttps://doi.org/10.13016/6jbc-ljwv
dc.identifier.urihttp://hdl.handle.net/1903/33701
dc.language.isoenen_US
dc.subject.pqcontrolledComputer scienceen_US
dc.subject.pquncontrolledCamera Egomotionen_US
dc.subject.pquncontrolledComputer Visionen_US
dc.subject.pquncontrolledInertial Odometryen_US
dc.subject.pquncontrolledRuled Surfaceen_US
dc.subject.pquncontrolledStructure from Motionen_US
dc.subject.pquncontrolledVisual Odometryen_US
dc.titleInertially Constrained Ruled Surfaces for Visual Odometryen_US
dc.typeThesisen_US

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