Hybrid activity and plan recognition for video streams. Granada, R., Pereira, R. F., Monteiro, J., Ruiz, D. D, Barros, R. C., & Meneguzzi, F. In Proceedings of the AAAI Workshop on Plan, Activity, and Intent Recognition (PAIR), 2017.
Hybrid activity and plan recognition for video streams [pdf]Paper  abstract   bibtex   
Computer-based human activity recognition of daily living has recently attracted much interest due to its applicability to ambient assisted living. Such applications require the automatic recognition of high-level activities composed of multiple actions performed by human beings in an environment. In this work, we address the problem of activity recognition in an indoor environment, focusing on a kitchen scenario. Unlike existing approaches that identify single actions from video sequences, we also identify the goal towards which the subject of the video is pursuing. Our hybrid approach combines a deep learning architecture to analyze raw video data and identify individual actions which are then processed by a goal recognition algorithm that uses a plan library describing possible overarching activities to identify the ultimate goal of the subject in the video. Experiments show that our approach achieves the state-of-the-art for identifying cooking activities in a kitchen scenario.

Downloads: 0