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Efficient Point-to-Subspace Query in ℓ1 with Application to Robust Face Recognition

Ju Sun; Yuqian Zhang; John N. Wright

Title:
Efficient Point-to-Subspace Query in ℓ1 with Application to Robust Face Recognition
Author(s):
Sun, Ju
Zhang, Yuqian
Wright, John N.
Date:
Type:
Articles
Department(s):
Electrical Engineering
Persistent URL:
Series:
Lecture Notes in Computer Science
Part Number:
7575
Book/Journal Title:
Computer Vision -- ECCV 2012: 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012: Proceedings, Part IV
Book Author:
Fitzgibbon, Andrew
Lazebnik, Svetlana
Perona, Pietro
Sato, Yoichi
Schmid, Cordelia
Publisher:
Springer
Publisher Location:
New York
Abstract:
Motivated by vision tasks such as robust face and object recognition, we consider the following general problem: given a collection of low-dimensional linear subspaces in a high-dimensional ambient (image) space, and a query point (image), efficiently determine the nearest subspace to the query in ℓ1 distance. We show in theory this problem can be solved with a simple two-stage algorithm: (1) random Cauchy projection of query and subspaces into low-dimensional spaces followed by efficient distance evaluation (ℓ1 regression); (2) getting back to the high-dimensional space with very few candidates and performing exhaustive search. We present preliminary experiments on robust face recognition to corroborate our theory.
Subject(s):
Computer science
Artificial intelligence
Publisher DOI:
https://doi.org/10.1007/978-3-642-33765-9_30
Item views
224
Metadata:
text | xml
Suggested Citation:
Ju Sun, Yuqian Zhang, John N. Wright, , Efficient Point-to-Subspace Query in ℓ1 with Application to Robust Face Recognition, Columbia University Academic Commons, .

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