2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Format:

Book

Author/Creator:

Institute of Electrical and Electronics Engineers, author, issuing body.

Language:

English

Subjects (All):

Pattern recognition systems--Congresses.

Pattern recognition systems.

Physical Description:

1 online resource

Place of Publication:

[Place of publication not identified] IEEE 2007

Language Note:

English

Summary:

Linear and affine subspaces are commonly used to describe appearance of objects under different lighting, viewpoint, articulation, and identity. A natural problem arising from their use is - given a query image portion represented as a point in some high dimensional space - find a subspace near to the query. This paper presents an efficient solution to the approximate nearest subspace problem for both linear and affine subspaces. Our method is based on a simple reduction to the problem of nearest point search, and can thus employ tree based search or locality sensitive hashing to find a near subspace. Further speedup may be achieved by using random projections to lower the dimensionality of the problem. We provide theoretical proofs of correctness and error bounds of our construction and demonstrate its capabilities on synthetic and real data. Our experiments demonstrate that an approximate nearest subspace can be located significantly faster than the exact nearest subspace, while at the same time it can find better matches compared to a similar search on points, in the presence of variations due to viewpoint, lighting etc.

Notes:

Bibliographic Level Mode of Issuance: Monograph

ISBN:

9781509090686

1509090681