HowToEat: Exploring Human Object Interaction and Eating Action in Eating Scenarios
Yingcheng Wang, Junwen Chen, Keiji Yanai · 2023
Recently, the analysis of multimedia of eating and diet has become a new trend in research. Detecting eating activities in videos and images is a basic requirement for further analysis. However, existing human-centric action detection tasks, such as human-object interaction detection and hand-object interaction detection lack the data in eating scenarios and annotations of eating actions. To fill this gap in research, we introduce a new large-scale dataset, HowToEat, which contains 66 days of videos in 12 eating scenarios, and 95k images with automatic annotations of hand-object interactions and eating actions. Based on the dataset, we propose an eating analysis system, which uses a single model to detect hand-object interaction and eating action at the same time.