Extremely Overlapping Vehicle Counting

The challenging problem that we explore in this paper is to precisely estimate the number of vehicles in an image of a traffic congestion situation. We start introducing TRANCOS, a novel database for extremely overlapping vehicle counting. It provides more than 1200 images where the number of vehicles and their locations have been annotated. We establish a clear experimental setup which will let others evaluate their own vehicle counting approaches. We also propose a novel evaluation metric, the Grid Average Mean absolute Error (GAME), which overcomes the limitations of previously proposed metrics for object counting. Finally, we perform an experimental validation, using the proposed TRANCOS dataset, for two types of vehicle counting strategies: counting by detection; and counting by regression. Our results show that counting by regression strategies are more precise localizing and estimating the number of vehicles. The TRANCOS database and the source code for reproducing the results are available at http://agamenon.tsc.uah.es/Personales/rlopez/data/trancos.