Graph kernels between point clouds

Details Graph kernels between point clouds Graph kernels between point clouds

2007-12-20

arxiv.org/abs/0712.3402v1

Computer Science

Learning

Scientific paper

Point clouds are sets of points in two or three dimensions. Most kernel methods for learning on sets of points have not yet dealt with the specific geometrical invariances and practical constraints associated with point clouds in computer vision and graphics. In this paper, we present extensions of graph kernels for point clouds, which allow to use kernel methods for such ob jects as shapes, line drawings, or any three-dimensional point clouds. In order to design rich and numerically efficient kernels with as few free parameters as possible, we use kernels between covariance matrices and their factorizations on graphical models. We derive polynomial time dynamic programming recursions and present applications to recognition of handwritten digits and Chinese characters from few training examples.

Affiliated with

Also associated with

No associations

Rating

Graph kernels between point clouds does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Graph kernels between point clouds, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Graph kernels between point clouds will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-3017