A generic framework for video understanding applied to group behavior recognition

This paper presents an approach to detect and track groups of people in video-surveillance applications, and to automatically recognize their behavior. This method keeps track of individuals moving together by maintaining a spacial and temporal group coherence. First, people are individually detected and tracked. Second, their trajectories are analyzed over a temporal window and clustered using the Mean-Shift algorithm. A coherence value describes how well a set of people can be described as a group. Furthermore, we propose a formal event description language. The group events recognition approach is successfully validated on 4 camera views from 3 datasets: an airport, a subway, a shopping center corridor and an entrance hall.Comment: (20/03/2012

Grounding Dynamic Spatial Relations for Embodied (Robot) Interaction

This paper presents a computational model of the processing of dynamic spatial relations occurring in an embodied robotic interaction setup. A complete system is introduced that allows autonomous robots to produce and interpret dynamic spatial phrases (in English) given an environment of moving objects. The model unites two separate research strands: computational cognitive semantics and on commonsense spatial representation and reasoning. The model for the first time demonstrates an integration of these different strands.Comment: in: Pham, D.-N. and Park, S.-B., editors, PRICAI 2014: Trends in Artificial Intelligence, volume 8862 of Lecture Notes in Computer Science, pages 958-971. Springe

Semantic business process management: a vision towards using semantic web services for business process management

Business process management (BPM) is the approach to manage the execution of IT-supported business operations from a business expert's view rather than from a technical perspective. However, the degree of mechanization in BPM is still very limited, creating inertia in the necessary evolution and dynamics of business processes, and BPM does not provide a truly unified view on the process space of an organization. We trace back the problem of mechanization of BPM to an ontological one, i.e. the lack of machine-accessible semantics, and argue that the modeling constructs of semantic Web services frameworks, especially WSMO, are a natural fit to creating such a representation. As a consequence, we propose to combine SWS and BPM and create one consolidated technology, which we call semantic business process management (SBPM