2020/05/16 by Aibek Musaev, Jiangping Wang, Musaev, Aibek +16
Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Gaze Tracking and Assistive Technology #IoT-based Smart Home Systems #Video Surveillance and Tracking Methods #cs.CV
paper · pdf · doi:10.48550/arxiv.2005.08009
openalex publication_date 2020/05/16 · arxiv created 2020/07/02 · arxiv updated 2020/07/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.