A Robust Approach to Camera Motion Classification
De Xu · Dianzi xuebao · 2006
Camera motion classification is an important issue in content-based video analysis.In this paper,a robust and hierarchical camera motion classification approach based on statistical learning is proposed.As Support Vector Machines(SVM) has a very good learning capacity with limited sample set without incorporating problem domain knowledge,in the first step,SVM is employed to classify camera motion operations into two classes:translation and non-translation operations.Then,rotation and zoom operations are distinguished using motion vectors' location and direction.The direction of translation operation is also identified.In the pre-processing step,cinematic rule is utilized to filter atypical noise and foreground motion noise.