The parking assist system (PAS) provides information of parking slots around the vehicle. As the demand for an autonomous system is increasing, intelligent PAS has been developed to park the vehicle without the driver’s intervention. To locate parking slots, most existing methods detect slot markings on the ground using an around-view monitoring (AVM) image. There are many types of parking slots of different shapes in the real world. Due to this fact, these methods either limit their target types or use predefined slot information of different types to cover the types. However, the approach using predefined slot information cannot handle more complex cases where the slot markings are connected to other line markings and the angle between slot marking is slightly different from the predefined settings. To overcome this problem, we propose a method to detect parking slots of various shapes without predefined type information. The proposed method is the first to introduce a free junction type feature to represent the structure of parking slot junction. Since the parking slot has a modular or repeated junction pattern at both sides, junction pair consisting of one parking slot can be detected using the free junction type feature. In this process, the geometrically symmetric characteristic of the junction pair is crucial to find each junction pair. The entrance of parking slot is reconstructed according to the structure of junction pair. Then, the vacancy of the parking slot is determined by a support vector machine. The Kalman tracker is applied for each detected parking slot to ensure stability of the detection in consecutive frames. We evaluate the performance of the proposed method by using manually collected datasets, captured in different parking environments. The experimental results show that the proposed method successfully detects various types of parking slots without predefined slot type information in different environments.

中文翻译：

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基于环视图像的实用自主代客泊车系统空车位识别方法

停车辅助系统 (PAS) 提供车辆周围停车位的信息。随着对自动驾驶系统的需求不断增加，智能 PAS 已被开发出来，无需驾驶员干预即可停放车辆。为了定位停车位，大多数现有方法使用环视监控 (AVM) 图像检测地面上的插槽标记。现实世界中有多种不同形状的停车位。由于这个事实，这些方法要么限制其目标类型，要么使用不同类型的预定义槽信息来覆盖类型。然而，使用预定义槽信息的方法无法处理更复杂的情况，即槽标记连接到其他线标记并且槽标记之间的角度与预定义设置略有不同。为了克服这个问题，我们提出了一种无需预定义类型信息即可检测各种形状停车位的方法。所提出的方法是第一个引入自由路口类型特征来表示停车位路口结构的方法。由于停车位在两侧具有模块化或重复的交叉点模式，因此可以使用自由交叉点类型特征检测由一个停车位组成的交叉点对。在这个过程中，结对的几何对称特性对于找到每个结对至关重要。停车位入口根据交叉口结构进行改造。然后，由支持向量机确定停车位的空缺。卡尔曼跟踪器应用于每个检测到的停车位，以确保连续帧中检测的稳定性。我们通过使用在不同停车环境中捕获的手动收集的数据集来评估所提出方法的性能。实验结果表明，所提出的方法在不同环境下无需预定义的车位类型信息即可成功检测各种类型的停车位。