An analysis of the combination of global and local models for activity recognition in videos
In this paper, we propose and analyze a framework of combining the global and local models for improving the activity recognition performance. Under the framework, several global-local-model combination methods are proposed for activity recognition. The advantages of combining the global and local models are also analyzed in detail. Experimental results demonstrate that the proposed framework can not only improve the recognition performance but also release the loads for parameter selection.