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2. Estimates of Temporal Edge Detection Filters in Human Vision
 
 # Estimates of Temporal Edge Detection Filters in Human Vision

  ![](/sites/default/files/styles/wide/public/publications/ted_teaser_0.PNG?itok=7F8Qmx66)

 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.



 ## Authors



[Pontus Ebelin](/person/pontus-ebelin)

Gyorgy Denes (The Perse School and University of Cambridge)

[Tomas Akenine-Möller](/person/tomas-akenine-moller)

Kalle Åström (Lund University)

Magnus Oskarsson (Lund University)

William H. McIlhagga (University of Bradford)

 

 

 ## Publication Date



Tuesday, January 30, 2024

 

 ## Published in



[ACM Transactions on Applied Perception](https://dl.acm.org/journal/tap)

 

 ## Research Area



[Applied Perception](/research-area/applied-perception)

 

 

 ## External Links



[Paper](https://dl.acm.org/doi/10.1145/3639052)

[Code for the flicker detection application](https://github.com/gdenes355/flicker_metric_ted)

 

 

 ## Uploaded Files



[Experiment introduction video. \[Warning: Do not watch if you suffer from epilepsy.\]](https://d1qx31qr3h6wln.cloudfront.net/publications/intro_video.mp4 "Open video in new window")2.62 MB