视频交通场景中的车辆检测:回顾与新视角

S. Gazzah, A. Mhalla, Najoua Essoukri Ben Amara
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引用次数: 0

摘要

车辆检测应用在减少道路交通事故数量方面发挥着重要作用。在同样的脉络下,本文倾向于总结车辆检测方法的最新进展。讨论了基于运动的方法和基于外观的方法。此外,还讨论了使用手工特征的挑战和限制。此外,我们比较了不同的方法被引用为新的视角在目标检测。使用两个视频进行的实验说明了基于深度学习的方法的鲁棒性,该方法将通用检测器专门化到特定场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vehicle detection on a video traffic scene: Review and new perspectives
Vehicle detection applications play an important role in the reduction of the number of road accidents. In the same vein, this paper tends to summarize the recent advances in vehicle detection approaches. Both the approaches based on motion and those based on appearance are dealt with. Also, the challenges and limitations of using handcraft features are discussed. Moreover, we compare different approaches cited as new perspectives in object detection. The experiments performed using two videos illustrate the robustness of the approach based on deep learning with specialization of the generic detector to a specific scene.
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