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Real-time object segmentation for visual object detection in dynamic scenes

机译:实时对象分割,用于动态场景中的视觉对象检测

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This paper presents a real-time object segmentation approach for visual object detection in dynamic scenes. This object segmentation approach is based on a novel general object feature which is defined subtly combining multiple low-level features and the uniqueness of the target object. Then the object segmentation approach is applied to detect vehicle and lane marking in dynamic scenes. Experiment results with test dataset extracted from real traffic scenes on highways and urban roads show that the approach proposed in this paper can achieve a high detection rate with an extreme low time cost.
机译:本文提出了一种用于动态场景中视觉对象检测的实时对象分割方法。该对象分割方法基于一种新颖的通用对象特征,该特征被巧妙地组合了多个低级特征和目标对象的唯一性而定义。然后将对象分割方法应用于动态场景中的车辆和车道标记检测。从高速公路和城市道路的真实交通场景中提取测试数据集的实验结果表明,本文提出的方法能够以极低的时间成本实现较高的检测率。

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