Visualizing Road Appearance Properties in Driving Video

dc.contributor.authorWang, Zheyuan
dc.contributor.authorZheng, Jiang Yu
dc.contributor.authorKilicarslan, Mehmet
dc.contributor.departmentDepartment of Computer & Information Science, School of Scienceen_US
dc.date.accessioned2017-06-21T16:24:22Z
dc.date.available2017-06-21T16:24:22Z
dc.date.issued2016-07
dc.description.abstractWith the increasing videos taken from driving recorders on thousands of cars, it is a challenging task to retrieve these videos and search for important information. The goal of this work is to mine certain critical road properties in a large scale driving video data set for traffic accident analysis, sensing algorithm development, and testing benchmark. Our aim is to condense video data to compact road profiles, which contain visual features of the road environment. By visualizing road edge and lane marks in the feature space with the reduced dimension, we will further explore the road edge models influenced by road and off-road materials, weather, lighting condition, etc.en_US
dc.eprint.versionAuthor's manuscripten_US
dc.identifier.citationWang, Z., Zheng, J. Y., & Kilicarslan, M. (2016, July). Visualizing Road Appearance Properties in Driving Video. In Nicograph International (NicoInt), 2016 (pp. 25-28). IEEE. http://dx.doi.org/10.1109/NicoInt.2016.5en_US
dc.identifier.urihttps://hdl.handle.net/1805/13138
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/NicoInt.2016.5en_US
dc.relation.journal2016 Nicograph International (NicoInt)en_US
dc.rightsIUPUI Open Access Policyen_US
dc.sourceAuthoren_US
dc.subjectdriving videoen_US
dc.subjectvisualizationen_US
dc.subjectdata compressionen_US
dc.titleVisualizing Road Appearance Properties in Driving Videoen_US
dc.typeConference proceedingsen_US
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