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The analysis of events in dynamic scenes has become an important and challenging problem increasingly in recent years. Events can be considered as obvious changes of important features with semantic meanings. From this viewpoint, the fundamental task of events analysis is to extract semantically meaningful changes and associate all of these basic motion patterns and changes with relevant visual concepts of moving objects in dynamic scenes. In this paper, we propose a method to extract lower level motion patterns and associate them with visual concepts respectively in a well-defined structure. Furthermore we also analyze latent spatial-temporal relationships among these basic visual concepts for event modeling and analysis. Finally, we present experimental results which prove the effectiveness of our approach on some real-world videos of dynamic scenes.

From Motion Patterns to Visual Concepts for Event Analysis in Dynamic Scenes