IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) is a scholarly archival journal published monthly. This journal covers traditional areas of computer vision and image understanding, all traditional areas of pattern analysis and recognition, and selected areas of machine intelligence. Read the full scope of TPAMI.
From the December 2015 issue
Scale and Rotation Invariant Matching Using Linearly Augmented Trees
By Hao Jiang, Tai-Peng Tian, and Stan Sclaroff
We propose a novel linearly augmented tree method for efficient scale and rotation invariant object matching. The proposed method enforces pairwise matching consistency defined on trees, and high-order constraints on all the sites of a template. The pairwise constraints admit arbitrary metrics while the high-order constraints use L1 norms and therefore can be linearized. Such a linearly augmented tree formulation introduces hyperedges and loops into the basic tree structure. But, different from a general loopy graph, its special structure allows us to relax and decompose the optimization into a sequence of tree matching problems that are efficiently solvable by dynamic programming. The proposed method also works on continuous scale and rotation parameters; we can match with a scale up to any large value with the same efficiency. Our experiments on ground truth data and a variety of real images and videos show that the proposed method is efficient, accurate and reliable.
Editorials and Announcements
- According to Thomson Reuters' 2013 Journal Citation Report, TPAMI has an impact factor of 5.694.
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- We are pleased to announce that David Forsyth, a professor at the University of Illinois at Urbana-Champaign, is the new Editor in Chief of IEEE Transactions on Pattern and Machine Intelligence starting in 2013. He was previously a member of the advisory board of TPAMI.
- TPAMI Essential Set now available
- State of the Journal (Jan 2015)
- Editor's Note (June 2013)
- Farewall State of the Journal (Jan 2013)
- Editor's Note (Jan 2013)
- Editor's Note (May 2012)
- Editor's Note (February 2012)
- State of the Journal (January 2012)
- Special Issue on Higher Order Graphical Models in Computer Vision (July 2015)
- Special Issue on Bayesian Nonparametrics (Feb 2015)
- TPAMI CVPR Special Section (Dec 2013)
- Special Section on Learning Deep Architectures (Aug 2013)
- In Memoriam: Mark Everingham (Nov 2012)
- Introduction to the Special Section on IEEE Conference on Computer Vision and Pattern Recognition (September 2012)
Call for Papers
- Special Issue on Learning with Shared Information for Computer Vision and Multimedia Analysis (PDF)
Submission deadline: February 1, 2016.
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