An automatic ego motion compensation based feature detection and correspondence algorithm is presented. For image sequences taken from a moving camera, feature displacement over consecutive frames can be approximately decomposed into two components: the displacement due to camera motion, which can be compensated for by image rotation, scaling, and translation; and the displacement due to object motion and/or perspective projection. The authors introduce a two-step approach. First, the motion of the camera is compensated for by using a computational vision based image registration algorithm. Then consecutive frames are transformed to the same coordinate system and the feature correspondence problem is solved as though for a stationary camera. Feature points are detected using a Gabor wavelet decomposition and a local interaction based algorithm. Methods for subpixel accuracy feature matching and tracking are introduced. Experimental results on a real image sequence are presented.
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