Temporal Scale and Shift Invariant Automatic Event Recognition using the Mellin Transform
This work addresses the problem of efficient and accurate event recognition in videos for applications where video speed may vary, which is an incremental improvement over existing methods.
The researchers tackled the problem of automatic event recognition in videos with varying speeds, achieving a significant improvement in recognition accuracy and filtering out almost all unwanted events. The exact numbers are not specified, but the method is claimed to be highly effective.
The Spatio-temporal holographic correlator combines the traditional 2D optical image correlation techniques with inhomogeneously broadened arrays of cold atoms to achieve 3D time-space correlation to realize automatic event recognition at an ultra-high speed. Here we propose a method to realize such event recognition for videos running at different speeds. With this method, we can highly improve recognition accuracy and filter almost all the unwanted events in the video database.