This paper proposes a scalable and robust algorithm to find connections between cameras in a large surveillance network, based solely on lighting variation. We show how to detect regions that are affected by lighting changes within each camera view, with limited data. Then, we establish the light-overlap connections and show that our algorithm can scale to hundreds of camera while maintaining high accuracy. We demonstrate our method on a campus network of 100 real cameras and 500 simulated cameras, and evaluate its accuracy and scalability.
CITATION STYLE
Zhu, M., Dick, A., & van den Hengel, A. (2017). Large-scale camera network topology estimation by lighting variation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10617 LNCS, pp. 455–467). Springer Verlag. https://doi.org/10.1007/978-3-319-70353-4_39
Mendeley helps you to discover research relevant for your work.