Local Single-Patch Features for Pose Estimation Using the Log-Polar Transform

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Abstract

This paper presents a local image feature, based on the log-polar transform which renders it invariant to orientation and scale variations. It is shown that this feature can be used for pose estimation of 3D objects with unknown pose, with cluttered background and with occlusion. The proposed method is compared to a previously published one and the new feature is found to be about as good or better as the old one for this task.