Rejection based multipath reconstruction for background estimation in SBMnet 2016 dataset
Diego Ortego, Juan C. SanMiguel, José M. Martínez · 2016
Background Estimation in video consists in extracting a foreground-free image from a set of training frames. In this paper, we overview a temporal-spatial block-level approach for background estimation in video and present their results in the SBMnet dataset. First, the employed approach uses a Temporal Analysis module to obtain a compact representation of the training data that is later clustered by a threshold-free technique to generate background candidates at each block location. Then, a Spatial Analysis module iteratively reconstructs the background using a multipath reconstruction guided by background smoothness constraints. The experimental results in the SBMnet dataset demonstrates the utility of the employed approach against stationary objects and its weaknesses when motion information is involved.