En-eye: A cooperative video fusion framework for traffic safety in intelligent transportation systems

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Abstract

Limited vision is a one of the most essential cause in traffic accidents. To guarantee the safety of vehicle operating, a series of matured assistance systems choose to deploy many special sensors. These solutions, however, only emphasize the equipment on a single vehicle. In some complex environment, detecting range would be limited within 50 m by various obstacles. Exchanging data among vehicles would be useful. But most current systems transfer a small amount of data, like vehicle operating states. In this paper, a smart-terminal-based framework named En-Eye is developed to enhance the traffic safety. En-Eye is proposed as a framework use smart terminals to construct a small-scope-network to exchange video data captured by camera in real time. Furthermore, video fusion is developed inside the framework for further analysis. Finally, an Android-based implementation of En-Eye framework has been achieved and work well in real environments.

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APA

Wu, T., & Zhang, L. (2017). En-eye: A cooperative video fusion framework for traffic safety in intelligent transportation systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10393 LNCS, pp. 652–657). Springer Verlag. https://doi.org/10.1007/978-3-319-65482-9_50

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