Image clustering with metric, local linear structure, and...

Image analysis – Pattern recognition – Classification

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Reexamination Certificate

active

10989967

ABSTRACT:
A system and a method are disclosed for clustering images of objects seen from different viewpoints. That is, given an unlabelled set of images of n objects, an unsupervised algorithm groups the images into N disjoint subsets such that each subset only contains images of a single object. The clustering method makes use of a broad geometric framework that exploits the interplay between the geometry of appearance manifolds and the symmetry of the 2D affine group.

REFERENCES:
patent: 5239596 (1993-08-01), Mahoney
patent: 6052485 (2000-04-01), Nelson et al.
patent: 2002/0097914 (2002-07-01), Yaung
Ng, et al. “On spectral clustering: analysis and an algorithm”, U.C.Berkeley, pp. 1-9, 2001.
Basri, et al. “Clustering appearances of 3D objects”, IEEE, pp. 1-8, 1998.
Huo “(A local smoothing and geodesic distance based clustering algorithm for high dimensional noisy data; utilizing embedded geometric structures”, GIT, pp. 1-5, Mar. 18, 2003.
Belhumeur, et al “What is the set of images of an object under all possible illumination conditions?”, International journal of computer vision, pp. 1-16.
PCT International Search Report and Written Opinion, PCT/US04/38347, Sep. 1, 2006, 7 pages.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Image clustering with metric, local linear structure, and... does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Image clustering with metric, local linear structure, and..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Image clustering with metric, local linear structure, and... will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-3757039

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.