论文标题
使用头部检测和跟踪热图迈向店内多人跟踪
Towards in-store multi-person tracking using head detection and track heatmaps
论文作者
论文摘要
计算机视觉算法正在跨广泛的行业实施，以实现技术创新。在本文中，我们研究了零售行业中基于计算机的客户跟踪的问题。为此，我们介绍了一个在办公室环境中从相机收集的数据集，参与者模仿了超市中客户的各种行为。此外，我们描述了该数据集使用基于头部跟踪模型跟踪参与者的说明性示例，以最大程度地减少因遮挡而导致的错误。此外，我们提出了一个模型，以根据他们的运动方式来识别客户和员工。使用在24小时内收集的超市中收集的现实世界数据集评估该模型，该数据集在训练过程中达到98％的精度和评估过程中的精度为93％。
Computer vision algorithms are being implemented across a breadth of industries to enable technological innovations. In this paper, we study the problem of computer vision based customer tracking in retail industry. To this end, we introduce a dataset collected from a camera in an office environment where participants mimic various behaviors of customers in a supermarket. In addition, we describe an illustrative example of the use of this dataset for tracking participants based on a head tracking model in an effort to minimize errors due to occlusion. Furthermore, we propose a model for recognizing customers and staff based on their movement patterns. The model is evaluated using a real-world dataset collected in a supermarket over a 24-hour period that achieves 98% accuracy during training and 93% accuracy during evaluation.
