000203873 001__ 203873
000203873 005__ 20180913062903.0
000203873 037__ $$aCONF
000203873 245__ $$aVisual attention in LDR and HDR images
000203873 269__ $$a2015
000203873 260__ $$c2015
000203873 336__ $$aConference Papers
000203873 520__ $$aRecent advances in high dynamic range (HDR) capturing and display technologies attracted a lot of interest to HDR imaging. Many issues that are considered as being resolved for conventional low dynamic range (LDR) images pose new challenges in HDR context. One of such issues is human visual attention, which has important applications in image and video compression, camera and displays manufacturing, artistic content creation, and advertisement. However, the impact of HDR imaging on visual attention and on the performance of saliency models is not well understood. Therefore, in this paper, we address this problem by creating a publicly available dataset of 46 HDR and corresponding LDR images with varying regions of interests, scenes, and dynamic range. We conducted eye tracking experiments and obtained fixation density maps, which demonstrate a significant difference in the way HDR and LDR capture attention of the observers.
000203873 700__ $$0(EPFLAUTH)241141$$aNemoto, Hiromi$$g241141
000203873 700__ $$aKorshunov, Pavel
000203873 700__ $$0245954$$aHanhart, Philippe$$g170391
000203873 700__ $$0240223$$aEbrahimi, Touradj$$g105043
000203873 7112_ $$a9th International Workshop on Video Processing and Quality Metrics for Consumer Electronics (VPQM)$$cChandler, Arizona, USA$$dFebruary 5-6, 2015
000203873 8564_ $$s5181168$$uhttps://infoscience.epfl.ch/record/203873/files/VPQM2015_HDREye.pdf$$yPreprint$$zPreprint
000203873 909C0 $$0252077$$pMMSPL
000203873 909CO $$ooai:infoscience.tind.io:203873$$pconf$$pSTI
000203873 917Z8 $$x170391
000203873 917Z8 $$x212659
000203873 917Z8 $$x170391
000203873 917Z8 $$x170391
000203873 937__ $$aEPFL-CONF-203873
000203873 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED
000203873 980__ $$aCONF