Learning Non-linear Calibration for Score Fusion with Applications to Image and Video Classification

@article{Ma2013LearningNC,
  title={Learning Non-linear Calibration for Score Fusion with Applications to Image and Video Classification},
  author={Tianyang Ma and Sangmin Oh and Amitha Perera and Longin Jan Latecki},
  journal={2013 IEEE International Conference on Computer Vision Workshops},
  year={2013},
  pages={323-330}
}
Image and video classification is a challenging task, particularly for complex real-world data. Recent work indicates that using multiple features can improve classification significantly, and that score fusion is effective. In this work, we propose a robust score fusion approach which learns non-linear score calibrations for multiple base classifier scores. Through calibration, original base classifiers scores are adjusted to reflect their true intrinsic accuracy and confidence, relative to… CONTINUE READING
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