Object-Based Goal Recognition Using Real-World Data

Goal and plan recognition of daily living activities has attracted much interest due to its applicability to ambient assisted living. Such applications require the automatic recognition of high-level activities based on multiple steps performed by human beings in an environment. In this work, we address the problem of plan and goal recognition of human activities in an indoor environment. Unlike existing approaches that use only actions to identify the goal, we use objects and their relations to identify the plan and goal towards which the subject in the video is pursuing. Our approach combines state-of-the-art object and relationship detection to analyze raw video data with a goal recognition algorithm to identify the subject's ultimate goal in the video. Experiments show that our approach identifies cooking activities in a kitchen scenario.