Recognizing and annotating the occurrence of team actions in observations of embodied agents has applications in surveillance and in training of military or sport teams. We descri...
Linus J. Luotsinen, Hans Fernlund, Ladislau Bö...
Spatio-temporal, geo-referenced datasets are growing rapidly, and will be more in the near future, due to both technological and social/commercial reasons. From the data mining vie...
This paper presents a novel learning method for human action detection in video sequences. The detecting problem is not limited in controlled settings like stationary background or...
In this paper, we propose a novel Spatiotemporal Interest Point (MC-STIP) detector based on the coherent motion pattern around each voxel in videos. Our detector defines the local...
Our goal is to segment multiple interacting and deforming agents in a video. Detectors often fail under large body deformation or agent entanglement. On the other hand, segmenting...