I was part of an international team of researchers from Canada, China and the United States who developed a a traffic surveillance dataset, MIO-TCD (http://tcd.miovision.com). The dataset consists of over half a million images acquired at different times of day and different periods of the year by 8,000 traffic cameras in Canada and the United States. The images cover a wide range of localization challenges and are representative of typical visual data captured today in urban traffic scenarios. Each moving object has been carefully outlined and identified to enable a quantitative comparison and ranking of various algorithms. This dataset aims to provide a rigorous benchmarking facility for training and testing existing and new algorithms for the localization of moving vehicles in traffic scenes.