Interactive Activity Learning from Trajectories with Qualitative Spatio‐Temporal Relation
Shengsheng Wang, Changji Wen, Yong Lai, Weiwei Liu, Dayou Liu · Chinese Journal of Electronics · 2015
Automatically analyzing interactions from video has gained much attention in recent years. Here anovel method has been proposed for analyzing interactions between two agents based on the trajectories. Previous works related to this topic are methods based on features, since they only extract features from objects. A method based on qualitative spatio-temporal relations isadopted which utilizes knowledge of the model (qualitative spatio-temporal relation calculi) instead of the original trajectory information. Based on the previous qualitatives patio-temporal relation works, such as Qualitative trajectory calculus (QTC), some new calculi are now proposed for long term and complex interactions. By the experiments, the results showed that our proposed calculi are very useful for representing interactions and improved the interaction learning more effectively.