Local feature extraction for video copy detection in a database
In this paper a new content-based copy identification method for video sequences is presented. It is robust to a number of image transformations and particulary robust to compression artifacts. A scale and rotation invariant local image descriptor for corner points in detected key frames is proposed based on a generalized Radon transform. In addition, a distance similarity metric is used that fuses intensity and geometry information to compare key frames extracted using a scene detection algorithm. Furthermore, to achieve low querying computational complexity a DP approach is employed. Experimental results demonstrate the effectiveness of our approach.