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Large-Scale Indoor Camera Positioning Using Fiducial Markers

dc.contributor.authorGarcía-Ruiz, Pablo
dc.contributor.authorRomero-Ramirez, Francisco J
dc.contributor.authorMuñoz-Salinas, Rafael
dc.contributor.authorMarín-Jiménez, Manuel J
dc.contributor.authorMedina-Carnicer, Rafael
dc.date.accessioned2024-12-02T07:30:59Z
dc.date.available2024-12-02T07:30:59Z
dc.date.issued2024-07
dc.identifier.citationGarcía-Ruiz, P.; Romero-Ramirez, F.J.; Muñoz-Salinas, R.; Marín-Jiménez, M.J.; Medina-Carnicer, R. Large-Scale Indoor Camera Positioning Using Fiducial Markers. Sensors 2024, 24, 4303. https://doi.org/10.3390/s24134303es
dc.identifier.issn1424-8220
dc.identifier.urihttps://hdl.handle.net/10115/42215
dc.description.abstractEstimating the pose of a large set of fixed indoor cameras is a requirement for certain applications in augmented reality, autonomous navigation, video surveillance, and logistics. However, accurately mapping the positions of these cameras remains an unsolved problem. While providing partial solutions, existing alternatives are limited by their dependence on distinct environmental features, the requirement for large overlapping camera views, and specific conditions. This paper introduces a novel approach to estimating the pose of a large set of cameras using a small subset of fiducial markers printed on regular pieces of paper. By placing the markers in areas visible to multiple cameras, we can obtain an initial estimation of the pair-wise spatial relationship between them. The markers can be moved throughout the environment to obtain the relationship between all cameras, thus creating a graph connecting all cameras. In the final step, our method performs a full optimization, minimizing the reprojection errors of the observed markers and enforcing physical constraints, such as camera and marker coplanarity and control points. We validated our approach using novel artificial and real datasets with varying levels of complexity. Our experiments demonstrated superior performance over existing state-of-the-art techniques and increased effectiveness in real-world applications. Accompanying this paper, we provide the research community with access to our code, tutorials, and an application framework to support the deployment of our methodology.es
dc.language.isoenges
dc.publisherMDPIes
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectindoor camera positioninges
dc.subjectcamera pose estimationes
dc.subjectfiducial markeres
dc.subjectvideo surveillancees
dc.titleLarge-Scale Indoor Camera Positioning Using Fiducial Markerses
dc.typeinfo:eu-repo/semantics/articlees
dc.identifier.doi10.3390/s24134303es
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses


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Atribución 4.0 InternacionalExcept where otherwise noted, this item's license is described as Atribución 4.0 Internacional