A moving corner detector for dynamic vehicular images

Introduces a moving corner detector for analysis of traffic movements. Image grey level corners are very important features in image analysis. In motion analysis, since the aperture problem does not exist at these points, the velocities at these places can be uniquely determined locally in theory. In a traffic scene, there are usually many moving corners, which can provide important clues for motion estimation. In this paper we introduce a moving corner detector that is composed of a corner detector and a moving edge detector. Since a corner point is also an edge point, the combination of these detectors provides information on moving corners. The corner detector is derived from Harris and Stephens´ (1988) combined corner and edge detector. The moving edge detector is realized through several frames. It combines both temporal and spatial information and is able to suppress noise, particularly the noise generated around strong background edge points. This moving corner detector can be computed locally and, therefore, can be implemented quite easily in parallel computing hardware