000218363 001__ 218363
000218363 005__ 20190317000441.0
000218363 037__ $$aCONF
000218363 245__ $$aNew Light Field Image Dataset
000218363 269__ $$a2016
000218363 260__ $$c2016
000218363 336__ $$aConference Papers
000218363 520__ $$aRecently, an emerging light field imaging technology, which enables capturing full light information in a scene, has gained a lot of interest. To design, develop, implement, and test novel algorithms in light field image processing and compression, the availability of suitable light field image datasets is essential. In this paper, a publicly available light field image dataset is introduced and described in details. The proposed dataset contains 118 light field images captured by using a Lytro Illum light field camera. Based on their content, acquired light field images were classified into ten different categories with various features covering wide range of potential usage, such as image compression and quality evaluation.
000218363 6531_ $$aLight Field Imaging
000218363 6531_ $$aLight Field Dataset
000218363 6531_ $$aPlenoptics
000218363 700__ $$0244457$$g206402$$aRerabek, Martin
000218363 700__ $$0240223$$g105043$$aEbrahimi, Touradj
000218363 7112_ $$dJune 6-8, 2016$$cLisbon, Portugal$$a8th International Conference on Quality of Multimedia Experience (QoMEX)
000218363 8564_ $$uhttp://mmspg.epfl.ch/EPFL-light-field-image-dataset$$zURL
000218363 8564_ $$uhttps://infoscience.epfl.ch/record/218363/files/Qomex2016_shortpaper.pdf$$zPublisher's version$$s3750685$$yPublisher's version
000218363 909C0 $$0252077$$pMMSPL
000218363 909CO $$pSTI$$ooai:infoscience.tind.io:218363$$qGLOBAL_SET$$pconf
000218363 917Z8 $$x206402
000218363 937__ $$aEPFL-CONF-218363
000218363 973__ $$rREVIEWED$$sACCEPTED$$aEPFL
000218363 980__ $$aCONF