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Estimates of Temporal Edge Detection Filters in Human Vision

Ebelin, Pontus LU orcid ; Denes, Gyorgy ; Akenine-Möller, Tomas LU ; Åström, Kalle LU orcid ; Oskarsson, Magnus LU orcid and McIlhagga, William H. (2024) In ACM Transactions on Applied Perception 21(2).
Abstract
Edge detection is an important process in human visual processing. However, as far as we know, few attempts have been made to map the temporal edge detection filters in human vision. To that end, we devised a user study and collected data from which we derived estimates of human temporal edge detection filters based on three different models, including the derivative of the infinite symmetric exponential function and temporal contrast sensitivity function. We analyze our findings using several different methods, including extending the filter to higher frequencies than were shown during the experiment. In addition, we show a proof of concept that our filter may be used in spatiotemporal image quality metrics by incorporating it into a... (More)
Edge detection is an important process in human visual processing. However, as far as we know, few attempts have been made to map the temporal edge detection filters in human vision. To that end, we devised a user study and collected data from which we derived estimates of human temporal edge detection filters based on three different models, including the derivative of the infinite symmetric exponential function and temporal contrast sensitivity function. We analyze our findings using several different methods, including extending the filter to higher frequencies than were shown during the experiment. In addition, we show a proof of concept that our filter may be used in spatiotemporal image quality metrics by incorporating it into a flicker detection pipeline. (Less)
Please use this url to cite or link to this publication:
@article{b29332e9-8a4c-4392-8d5a-2949937eb450,
  abstract     = {{Edge detection is an important process in human visual processing. However, as far as we know, few attempts have been made to map the temporal edge detection filters in human vision. To that end, we devised a user study and collected data from which we derived estimates of human temporal edge detection filters based on three different models, including the derivative of the infinite symmetric exponential function and temporal contrast sensitivity function. We analyze our findings using several different methods, including extending the filter to higher frequencies than were shown during the experiment. In addition, we show a proof of concept that our filter may be used in spatiotemporal image quality metrics by incorporating it into a flicker detection pipeline.}},
  author       = {{Ebelin, Pontus and Denes, Gyorgy and Akenine-Möller, Tomas and Åström, Kalle and Oskarsson, Magnus and McIlhagga, William H.}},
  issn         = {{1544-3558}},
  language     = {{eng}},
  month        = {{01}},
  number       = {{2}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  series       = {{ACM Transactions on Applied Perception}},
  title        = {{Estimates of Temporal Edge Detection Filters in Human Vision}},
  url          = {{http://dx.doi.org/10.1145/3639052}},
  doi          = {{10.1145/3639052}},
  volume       = {{21}},
  year         = {{2024}},
}