A large scale dataset for classification of vehicles in urban traffic scenes

H. S. Bharadwaj, S. Biswas, K. Ramakrishnan
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引用次数: 12

Abstract

Vehicle Classification has been a well-researched topic in the recent past. However, advances in the field have not been corroborated with deployment in Intelligent Traffic Management, due to non-availability of surveillance quality visual data of vehicles in urban traffic junctions. In this paper, we present a dataset aimed at exploring Vehicle Classification and related problems in dense, urban traffic scenarios. We present our on-going effort of collecting a large scale, surveillance quality, dataset of vehicles seen mostly on Indian roads. The dataset is an extensive collection of vehicles under different poses, scales and illumination conditions in addition to a smaller set of Near Infrared spectrum images for night time and low light traffic surveillance. We will make the dataset available for further research in this area. We propose and evaluate few baseline algorithms for the task of vehicle classification on this dataset. We also discuss challenges and potential applications of the data.
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城市交通场景车辆分类的大规模数据集
车辆分类是近年来研究较多的一个课题。然而,由于无法获得城市交通路口车辆的监控质量视觉数据,该领域的进展尚未得到智能交通管理部署的证实。在本文中,我们提出了一个数据集,旨在探索密集城市交通场景下的车辆分类和相关问题。我们展示了我们正在进行的收集大规模、高质量、主要在印度道路上看到的车辆数据集的努力。该数据集广泛收集了不同姿态、尺度和照明条件下的车辆,此外还有一组较小的近红外光谱图像,用于夜间和低光交通监控。我们将为这一领域的进一步研究提供数据集。在此数据集上,我们提出并评估了几种用于车辆分类任务的基线算法。我们还讨论了这些数据的挑战和潜在应用。
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