Understanding Room Interiors Using Associative Memory

We propose method of understanding the real environment with data from visual information. Recently, we have needed a robot system that handles difficult problems facing nursing care, other medical fields, welfare, and so on. However, it is difficult to understand and adapt to the surrounding environment from real images. We constructed a computer system for understanding the real environment with a neural network model of associative memories. We built this modeling system that associated the category of an unknown object in the virtual room interior. This system saved data for many contexts for environmental knowledge. The experimental results indicate the effectiveness of the system. This paper provides a quick overview of the system applied to object recognition.