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1 MAGRIT - Visual Augmentation of Complex Environments INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications 2 CAMPAR - Computer Aided Medical Procedures & Augmented Reality 3 EPFL - Ecole Polytechnique Fédérale de Lausanne

Abstract : Activity recognition has primarily addressed the identification of either actions or well-defined interactions among objects in a scene. In this work, we extend the scope to the study of workflow monitoring. In a workflow, ordered groups of activities phases with different durations take place in a constrained environment and create temporal patterns across the workflow instances. We address the problem of recognizing phases, based on exemplary recordings. We propose to use Workflow-HMMs, a form of HMMs augmented with phase probability variables that model the complete workflow process. This model takes into account the full temporal context which improves on-line recognition of the phases, especially in case of partial labeling. Targeted applications are workflow monitoring in hospitals and factories, where common action recognition approaches are difficult to apply. To avoid interfering with the normal workflow, we capture the activity of a room with a multiple-camera system. Additionally, we propose to rely on real-time low-level features 3D motion flow to maintain a generic approach. We demonstrate our methods on sequences from medical procedures performed in a mock-up operating room. The sequences follow a complex workflow, containing various alternatives.





Autor: Nicolas Padoy - Diana Mateus - Daniel Weinland - Marie-Odile Berger - Nassir Navab -

Fuente: https://hal.archives-ouvertes.fr/



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