Unifying real-time multi-vehicle tracking and categorization

F. Bardet, T. Chateau, D. Ramadasan
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引用次数: 11

Abstract

This paper addresses real-time automatic visual tracking and classification of a variable number of vehicles in traffic. This off-board surveillance device may cooperate with on-board Advanced Driver Assistance Systems (ADAS), extending its measurement range to the areas of the road that are not in the car sensors field-of-view (in a curve or an intersection). Tracking results also are useful for statistical trajectory analysis, devoted to understanding and improving user-user and user-infrastructure interactions. As a main contribution, this paper proposes to unify vehicle tracking and classification in a single processing step. This paper also addresses a vehicle anisotropic distance measurement based on the vehicle 3D geometric model. Real time tracking results are shown and discussed on road sequences involving various types of vehicles such as motorcycles, cars, light trucks and heavy trucks.
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统一实时多车跟踪和分类
本文研究了交通中可变数量车辆的实时自动视觉跟踪与分类。这种车载监控设备可以与车载高级驾驶辅助系统(ADAS)配合使用,将其测量范围扩展到汽车传感器视野之外的道路区域(如弯道或十字路口)。跟踪结果对统计轨迹分析也很有用,致力于理解和改进用户-用户和用户-基础设施的交互。本文的主要贡献是将车辆跟踪和分类统一到一个处理步骤中。本文还研究了基于车辆三维几何模型的车辆各向异性距离测量方法。实时跟踪结果显示和讨论道路序列涉及各种类型的车辆,如摩托车,汽车,轻型卡车和重型卡车。
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