A logic-based calculus of events
New Generation Computing
Learning, detection and representation of multi-agent events in videos
Artificial Intelligence
Human Behavior Classification Using Multiple Views
SETN '08 Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications
Knowledge representation concepts for automated SLA management
Decision Support Systems
Chronicle recognition improvement using temporal focusing and hierarchization
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Event detection and recognition for semantic annotation of video
Multimedia Tools and Applications
PRONTO: support for real-time decision making
Proceedings of the 5th ACM international conference on Distributed event-based system
Initial steps towards run-time support for norm-governed systems
COIN@AAMAS'10 Proceedings of the 6th international conference on Coordination, organizations, institutions, and norms in agent systems
Video semantic concept detection using ontology
Proceedings of the Third International Conference on Internet Multimedia Computing and Service
Probabilistic event calculus based on Markov logic networks
RuleML'11 Proceedings of the 5th international conference on Rule-based modeling and computing on the semantic web
Using constraint optimization for conflict resolution and detail control in activity recognition
AmI'11 Proceedings of the Second international conference on Ambient Intelligence
Event processing under uncertainty
Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems
Ubiquitous Agents for Ambient Ecologies
Pervasive and Mobile Computing
The scientific contribution of marek sergot
Logic Programs, Norms and Action
| Hi-index | 0.00 |
We have been developing a system for recognising human activity given a symbolic representation of video content. The input of our system is a set of time-stamped short-term activities detected on video frames. The output of our system is a set of recognised long-term activities, which are pre-defined temporal combinations of short-term activities. The constraints on the short-term activities that, if satisfied, lead to the recognition of a long-term activity, are expressed using a dialect of the Event Calculus. We illustrate the expressiveness of the dialect by showing the representation of several typical complex activities. Furthermore, we present a detailed evaluation of the system through experimentation on a benchmark dataset of surveillance videos.