Miho Takayanagi, Osamu Fukuda, Nobuhiko Yamaguchi, Hiroshi Okumura, Anik Nur Handayani
This paper proposes a method that combines a relevance model with general object recognition. This method can detect general objects and recognize scenes. Based on scene recognition, object detection accuracy can be improved, and the product search time at a store can be reduced. To recognize a scene from the detected objects, the proposed algorithm uses a relevance model constructed by a Bayesian network. Experiments were conducted to verify the effectiveness of the proposed method. In the experiments, the stock status of the products and the categories of the corners were estimated. The results confirmed that the stock status of the products and corner categories were correctly estimated. © 2021 IEEE.
Saga University, Graduate School Of Science And Engineering, Saga, 840-8502, Japan; Universitas Negeri Malang, Department Of Electrical Engineering, Jalan Semarang 5, East Java, 65145, Indonesia
