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Learning What and How of Contextual Models for Scene Labeling

  • Arpit Jain
  • Abhinav Gupta
  • Larry S. Davis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6314)

Abstract

We present a data-driven approach to predict the importance of edges and construct a Markov network for image analysis based on statistical models of global and local image features. We also address the coupled problem of predicting the feature weights associated with each edge of a Markov network for evaluation of context. Experimental results indicate that this scene dependent structure construction model eliminates spurious edges and improves performance over fully-connected and neighborhood connected Markov network.

Keywords

Training Dataset Training Image Contextual Model Feature Weight Contextual Relationship 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Arpit Jain
    • 1
  • Abhinav Gupta
    • 2
  • Larry S. Davis
    • 1
  1. 1.University of Maryland College Park
  2. 2.Carnegie Mellon UniversityPittsburgh

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