A Framework For Automated Analysis of Surrogate Measures of Safety from Video using Deep Learning Techniques

Autor: Jensen, Morten Bornø, Ahrnbom, Martin, Kruithof, Maarten, Åström, Kalle, Nilsson, Mikael, Ardö, Håkan, Laureshyn, Aliaksei, Johnsson, Carl, Moeslund, Thomas B.

Publikováno v: Jensen, M B, Ahrnbom, M, Kruithof, M, Åström, K, Nilsson, M, Ardö, H, Laureshyn, A, Johnsson, C & Moeslund, T B 2019, ' A Framework For Automated Analysis of Surrogate Measures of Safety from Video using Deep Learning Techniques ', Transportation Research Board. Annual Meeting Proceedings, pp. 281-306 .

Traffic surveillance and monitoring are gaining a lot of attention as a result of anincrease of vehicles on the road and a desire to minimize accidents. In order to minimizeaccidents and near-accidents, it is important to be able to judge the safety

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::bb601f56fa82413995ddf38983e1463f
https://vbn.aau.dk/da/publications/ad7594a0-9d00-4013-a9b5-b4e4938499b6

Author Index.

Publikováno v: 2016 IEEE Conference on Computer Vision & Pattern Recognition Workshops (CVPRW); 2016, p1616-1623, 8p