A Spatio-temporal Extension of the SUSAN-Filter

This paper proposes a detector for spatio-temporal interest points. Interest point detection is a common technique in computer vision to extract salient regions and represent them by a single point for further processing. But while many algorithms exist for static images, there is hardly any method to obtain interest points from image sequences for the representation of salient motion. Here we introduce SUSANinTime, an extension of the well known SUSAN algorithm from 2D to 2D+1D, where the third dimension is time. While SUSAN-2D extracts edgeand corner points, SUSANinTime detects basic events such as turning points of object trajectories. To find out the type and saliency of the detected events, we analyze the second order statistics of the spatio-temporal volume surrounding the interest points in real world image sequences.