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ICIP
1998
IEEE
16 years 1 months ago
Reducing the Computational Complexity of a Map Post-Processing Algorithm for Video Sequences
Maximum a posteriori (MAP) filtering using the HuberMarkov random field (HMRF) image model has been shown in the past to be an effective method of reducing compression artifacts i...
Mark A. Robertson, Robert L. Stevenson
DAGM
2008
Springer
15 years 1 months ago
MAP-Inference for Highly-Connected Graphs with DC-Programming
The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-fun...
Jörg H. Kappes, Christoph Schnörr
IJCV
2008
172views more  IJCV 2008»
14 years 11 months ago
Nonparametric Bayesian Image Segmentation
Image segmentation algorithms partition the set of pixels of an image into a specific number of different, spatially homogeneous groups. We propose a nonparametric Bayesian model f...
Peter Orbanz, Joachim M. Buhmann
ACL
2010
14 years 10 months ago
Identifying Non-Explicit Citing Sentences for Citation-Based Summarization
Identifying background (context) information in scientific articles can help scholars understand major contributions in their research area more easily. In this paper, we propose ...
Vahed Qazvinian, Dragomir R. Radev
BMVC
2010
14 years 10 months ago
Motion Coherent Tracking with Multi-label MRF optimization
We present a novel off-line algorithm for target segmentation and tracking in video. In our approach, video data is represented by a multi-label Markov Random Field model, and seg...
David Tsai, Matthew Flagg, James M. Rehg