NDLI: Online robust image alignment via iterative convex optimization

Content Provider	IEEE Xplore Digital Library
Author	Yi Wu Bin Shen Haibin Ling
Copyright Year	2012
Description	Author affiliation: Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA (Bin Shen) \|\| Center for Data Analytics & Biomedical Informatics, Computer & Information Science Department, Temple University, Philadelphia, PA 19122, USA (Yi Wu; Haibin Ling)
Abstract	In this paper we study the problem of online aligning a newly arrived image to previously well-aligned images. Inspired by recent advances in batch image alignment using low rank decomposition [ ], we treat the newly arrived image, after alignment, as being linearly and sparsely reconstructed by the well-aligned ones. The task is accomplished by a sequence of convex optimization that minimizes the l\-norm. After that, online basis updating is pursued in two different ways: (1) a two-stage incremental alignment for joint registration of a large image dataset which is known a prior, and (2) a greedy online alignment of dynamically increasing image sequences, such as in the tracking scenario. In (1), we first sequentially collect basis images that are easily aligned by checking their reconstruction residuals, followed by the second stage where all images are re-aligned one-by-one using the collected basis set. In (2), during the tracking process, we dynamically enrich the image basis set by the new target if it significantly distinguishes itself from existing basis images. While inheriting the benefits of sparsity, our method enjoys the great time efficiency and therefore be capable of dealing with large image set and real time tasks such as visual tracking. The efficacy of the proposed online robust alignment algorithm is verified with extensive experiments on image set alignment and visual tracking, in reference with state-of-the-art methods.
Starting Page	1808
Ending Page	1814
File Size	761892
Page Count	7
File Format	PDF
ISBN	9781467312264
ISSN	10636919
e-ISBN	9781467312288
e-ISBN	9781467312271
DOI	10.1109/CVPR.2012.6247878
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Target tracking Visualization Face Robustness Joints Image reconstruction Convex functions
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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