Publikation: Occlusion-Aware Depth Estimation Using Sparse Light Field Coding
Dateien
Datum
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
DOI (zitierfähiger Link)
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Publikationsstatus
Erschienen in
Zusammenfassung
Disparity estimation for multi-layered light fields can robustly be performed with a statistical analysis of sparse light field coding coefficients [7]. The key idea is to explain each epipolar plane image patch with a dictionary composed of atoms with known disparity values. We significantly improve upon their approach in two ways. First, we reduce the number of necessary dictionary atoms, improving descriptive quality of each and reducing time complexity by an order of magnitude. Second, we introduce a way to explicitly handle occlusions, which is the main drawback in the previous work. Experiments demonstrate that we thus achieve substantially better results on both Lambertian as well as multi-layered scenes.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
Schlagwörter
Konferenz
Rezension
Zitieren
ISO 690
JOHANNSEN, Ole, Antonin SULC, Bastian GOLDLÜCKE, 2016. Occlusion-Aware Depth Estimation Using Sparse Light Field Coding. 38th International Conference, GCPR 2016. Hannover, 12. Sept. 2016 - 15. Sept. 2016. In: ROSENHAHN, Bodo, ed. and others. Pattern Recognition : 38th International Conference, GCPR 2016, Hannover, Germany, September 12-15, 2016, Proceedings. Cham: Springer, 2016, pp. 207-218. Lecture Notes in Computer Science. 9796. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-319-45885-4. Available under: doi: 10.1007/978-3-319-45886-1_17BibTex
@inproceedings{Johannsen2016-08-27Occlu-35787, year={2016}, doi={10.1007/978-3-319-45886-1_17}, title={Occlusion-Aware Depth Estimation Using Sparse Light Field Coding}, number={9796}, isbn={978-3-319-45885-4}, issn={0302-9743}, publisher={Springer}, address={Cham}, series={Lecture Notes in Computer Science}, booktitle={Pattern Recognition : 38th International Conference, GCPR 2016, Hannover, Germany, September 12-15, 2016, Proceedings}, pages={207--218}, editor={Rosenhahn, Bodo}, author={Johannsen, Ole and Sulc, Antonin and Goldlücke, Bastian} }
RDF
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/35787"> <dc:creator>Goldlücke, Bastian</dc:creator> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2016-10-31T09:43:33Z</dc:date> <dc:creator>Johannsen, Ole</dc:creator> <dc:contributor>Sulc, Antonin</dc:contributor> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2016-10-31T09:43:33Z</dcterms:available> <foaf:homepage rdf:resource="http://localhost:8080/"/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:contributor>Johannsen, Ole</dc:contributor> <dcterms:abstract xml:lang="eng">Disparity estimation for multi-layered light fields can robustly be performed with a statistical analysis of sparse light field coding coefficients [7]. The key idea is to explain each epipolar plane image patch with a dictionary composed of atoms with known disparity values. We significantly improve upon their approach in two ways. First, we reduce the number of necessary dictionary atoms, improving descriptive quality of each and reducing time complexity by an order of magnitude. Second, we introduce a way to explicitly handle occlusions, which is the main drawback in the previous work. Experiments demonstrate that we thus achieve substantially better results on both Lambertian as well as multi-layered scenes.</dcterms:abstract> <dcterms:issued>2016-08-27</dcterms:issued> <dc:contributor>Goldlücke, Bastian</dc:contributor> <dc:language>eng</dc:language> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/35787"/> <dcterms:title>Occlusion-Aware Depth Estimation Using Sparse Light Field Coding</dcterms:title> <dc:creator>Sulc, Antonin</dc:creator> </rdf:Description> </rdf:RDF>