In order to develop a high-level description of events unfolding in a typical surveillance scenario, each successfully tracked event must be classified into type and behaviour. I...
We propose a new approach for video event learning. The only hypothesis is the availability of tracked object attributes. The approach incrementally aggregates the attributes and r...
We present a novel approach to representing and recognizing composite video events. A composite event is specified by a scenario, which is based on primitive events and their tem...
We explore how recent data-mining-based tools developed in domains such as biomedicine or text-mining for extracting interesting knowledge from sequence data could be applied to pe...
Gilbert Ritschard, Alexis Gabadinho, Nicolas S. M&...
In this paper, we model multi-agent events in terms of a temporally varying sequence of sub-events, and propose a novel approach for learning, detecting and representing events in...