• Corpus ID: 231846371

Predicting Eye Fixations Under Distortion Using Bayesian Observers

@article{Tu2021PredictingEF,
  title={Predicting Eye Fixations Under Distortion Using Bayesian Observers},
  author={Zhengzhong Tu},
  journal={ArXiv},
  year={2021},
  volume={abs/2102.03675}
}
Visual attention is very an essential factor that affects how human perceives visual signals. This report investigates how distortions in an image could distract human’s visual attention using Bayesian visual search models, specifically, Maximum-a-posteriori (MAP) [1] [2] and Entropy Limit Minimization (ELM) [3], which predict eye fixation movements based on a Bayesian probabilistic framework. Experiments on modified MAP and ELM models on JPEG-compressed images containing blocking or ringing… 
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