Sciweavers

Share
ICCV
2005
IEEE

Non-Orthogonal Binary Subspace and Its Applications in Computer Vision

9 years 1 months ago
Non-Orthogonal Binary Subspace and Its Applications in Computer Vision
This paper presents a novel approach that represents an image or a set of images using a nonorthogonal binary subspace (NBS) spanned by boxlike base vectors. These base vectors possess the property that the inner product operation with them can be computed very efficiently. We investigate the optimized orthogonal matching pursuit method for finding the best NBS base vectors. It is demonstrated in this paper how the NBS based expansion can be applied to speed up several common computer vision algorithms, including normalized cross correlation (NCC), sum of squared difference (SSD) matching, appearance subspace projection and subspace-based object recognition. Promising experimental results on facial and natural images are demonstrated in this paper.
Hai Tao, Ryan Crabb, Feng Tang
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where ICCV
Authors Hai Tao, Ryan Crabb, Feng Tang
Comments (0)
books