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 July 2015 issue
Learning Weighted Lower Linear Envelope Potentials in Binary Markov Random Fields
By Stephen Gould
Markov random fields containing higher-order terms are becoming increasingly popular due to their ability to capture complicated relationships as soft constraints involving many output random variables. In computer vision an important class of constraints encode a preference for label consistency over large sets of pixels and can be modeled using higher-order terms known as lower linear envelope potentials. In this paper we develop an algorithm for learning the parameters of binary Markov random fields with weighted lower linear envelope potentials. We first show how to perform exact energy minimization on these models in time polynomial in the number of variables and number of linear envelope functions. Then, with tractable inference in hand, we show how the parameters of the lower linear envelope potentials can be estimated from labeled training data within a max-margin learning framework. We explore three variants of the lower linear envelope parameterization and demonstrate results on both synthetic and real-world problems.
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.
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- State of the Journal (Jan 2015)
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- Editor's Note (Jan 2013)
- Editor's Note (May 2012)
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- Special Issue on Higher Order Graphical Models in Computer Vision (July 2015)
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- In Memoriam: Mark Everingham (Nov 2012)
- Introduction to the Special Section on IEEE Conference on Computer Vision and Pattern Recognition (September 2012)
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