Keywords:Behavior analysis system, marketing analysis, action localization
It is important in marketing analysis to understand customer behavior in front of in-store displays and their subsequent actions. On the other hand, there are ongoing studies on action detection techniques using deep learning, but what can be obtained by such techniques are primitive action labels such as "standing" and "walking," and further innovations are needed to extract detailed store behavior. In this study, we propose a system that analyzes the status of the display at the entrance of a restaurant and subsequent user behavior by combining a deep learning model for action detection (SlowFast), and a multi-person tracking model (FairMOT). The effectiveness of the system is discussed through evaluation using images of people entering a restaurant.
Authentication for paper PDF access
A password is required to view paper PDFs. If you are a registered participant, please log on the site from Participant Log In.
You could view the PDF with entering the PDF viewing password bellow.