Lidar assisted Depth Estimation for Thermal Cameras

Cite This

Files in this item

Checksum: MD5:47103798ad3ee85db9df23039307a335

JANDELEIT, Julian, 2022. Lidar assisted Depth Estimation for Thermal Cameras [Bachelor thesis]. Konstanz: Universität Konstanz

@mastersthesis{Jandeleit2022Lidar-57714, title={Lidar assisted Depth Estimation for Thermal Cameras}, year={2022}, address={Konstanz}, school={Universität Konstanz}, author={Jandeleit, Julian} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dspace:isPartOfCollection rdf:resource=""/> <dc:rights>terms-of-use</dc:rights> <dcterms:abstract xml:lang="eng">Depth- and pose estimation are classical problems in computer vision. Estimating the depth of thermal cameras can be achieved by estimating the camera poses in an independently captured lidar scan. In underground environments and animal behavior, thermal cameras are often used instead of classical RGB cameras. But existing methods for RGB pose estimation do not necessarily need to be effective for thermal cameras, because their working mode and data are different. This is the case for subterranean cave environments. Thermal cameras can be used to capture animal behavior in dark caves. This is what this paper is focused on. This work provides a systematic approach to the alignment of lidar and thermal image information. We use the Ushichka dataset as an exemplary study case. Classical computer vision techniques like Direct Linear Triangulation and Space Carving are are applied to the dataset. We find that the classical methods do not work here as expected and provide a semi-automatic framework, called DMCP, to solve the registration. Finally, different approaches are compared in order to point out in which way a fully automatic registration might be possible.</dcterms:abstract> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dspace:hasBitstream rdf:resource=""/> <dcterms:available rdf:datatype="">2022-06-01T08:23:09Z</dcterms:available> <dc:creator>Jandeleit, Julian</dc:creator> <dcterms:title>Lidar assisted Depth Estimation for Thermal Cameras</dcterms:title> <bibo:uri rdf:resource=""/> <dc:contributor>Jandeleit, Julian</dc:contributor> <dc:language>eng</dc:language> <dcterms:issued>2022</dcterms:issued> <dcterms:isPartOf rdf:resource=""/> <dcterms:rights rdf:resource=""/> <dc:date rdf:datatype="">2022-06-01T08:23:09Z</dc:date> <dcterms:hasPart rdf:resource=""/> </rdf:Description> </rdf:RDF>

Downloads since Jun 1, 2022 (Information about access statistics)

Jandeleit_2-vdtn88xxgotj1.pdf 78

This item appears in the following Collection(s)

Search KOPS


My Account