Fredrik Vikstén

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We have developed a system which integrates the information output from several pose estimation algorithms and from several views of the scene. It is tested in a real setup with a robotic manipulator. It is shown that integrating pose estimates from several algorithms increases the overall performance of the pose estimation accuracy as well as the(More)
This paper presents a local image feature, based on the logpolar 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(More)
Recent years have seen advances in the estimation of full 6 degree-of-freedom object pose from a single 2D image. These advances have often been presented as a result of, or together with, a new local image descriptor. This paper examines how the performance for such a system varies with choice of local descriptor. This is done by comparing the performance(More)
We present a novel local descriptor for range data that can describe one or more planes or lines in a local region. It is possible to recover the geometry of the described local region and extract the size, position and orientation of each local plane or line-like structure from the descriptor. This gives the descriptor a property that other popular local(More)
This paper presents a novel representation for 3D shapes in terms of planar surface patches and their boundaries. The representation is based on a tensor formalism similar to the usual orientation tensor but extends this concept by using projective spaces and a fourth order tensor, even though the practical computations can be made in normal matrix algebra.(More)
Recent years have seen a lot of work on local descriptors. In all published comparisons or evaluations, the now quite well-known SIFT-descriptor has been one of the top performers. For the application of object pose estimation, one comparison showed a local descriptor, called the Patch-Duplet, of equal or better performance than SIFT. This paper examines(More)
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