This paper proposes a customer interest estimation method using security camera to meet the demand of the retail industry. In the field of retail industry, it is considered that the understanding of customers’ interests in the real store can be used for various marketing activities such as the product development and the layout of the store. Then, it is important to pay attention to customers’ behavior in the real store. Their behavior is often recorded by the cameras installed in the store for security purposes. A method for estimating their interests from the videos of the security camera is presented in this paper. The novelty of our method is three-fold. Firstly, the experimental data of subjects in our group were taken by using the security camera already installed in the real store. Secondly, we used a pre-trained posture estimation model and treated the results as the features to be trained by a two-layer neural network model. Finally, a professional have annotated the subjects’ interests. The effectiveness of our method was confirmed by comparing with benchmark supervised machine learning models.
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