Video display device and control method
US-2019379860-A1 · Dec 12, 2019 · US
US11710467B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11710467-B2 |
| Application number | US-202217694356-A |
| Country | US |
| Kind code | B2 |
| Filing date | Mar 14, 2022 |
| Priority date | May 7, 2021 |
| Publication date | Jul 25, 2023 |
| Grant date | Jul 25, 2023 |
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In one embodiment, a computing system may access an image to be displayed by a display. The system may determine one or more first characteristics associated with a content of the image. The one or more first characteristics may include a contrast level of the content of the image with respect to a background of the image. The system may determine a first display persistence time period for the display to display the image based on the one or more first characteristics associated with the content of the image. The system may configure the display to display the image using the first display persistence time period.
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What is claimed is: 1. A method, by a computing system, comprising: accessing an image to be displayed by a display; determining one or more first characteristics associated with a content of the image, wherein the one or more first characteristics comprise a contrast level of the content of the image with respect to a background of the image, and wherein the contrast level is determined based on pixel values associated with the content of the image and (1) pixel values associated with a background portion of the image or (2) a brightness level associated with a real-world scene; determining a first display persistence time period for the display to display the image based on the one or more first characteristics associated with the content of the image; and configuring the display to display the image using the first display persistence time period. 2. The method of claim 1 , further comprising: determining, using a prediction model, a likelihood level of the image to have visible motion blur when displayed by the display. 3. The method of claim 2 , wherein the prediction model comprises a mapping model that maps the one or more first characteristics to the first display persistence time period based on the likelihood level of the image to have the visible motion blur when displayed by the display. 4. The method of claim 3 , wherein the mapping model comprises a lookup table or a transfer function that maps the one or more first characteristics to the first display persistence time period. 5. The method of claim 1 , wherein the content of the image is associated with a foveated region encompassing a gazing point of a user, and wherein a portion of the image falling outside the foveated region is excluded from determining the one or more first characteristics associated with the content of the image. 6. The method of claim 1 , wherein the first display persistence time period for the image comprises an absolute time period value or a display duty cycle in percentage. 7. The method of claim 1 , further comprising: determining, using a head tracking system, a head motion velocity of a user; determining a second display persistence time period for the image based on the head motion velocity of the user; determining an optimized display persistence time period based on the first display persistence time period and the second display persistence time period; and configuring the display to display the image using the optimized display persistence time period. 8. The method of claim 7 , wherein the optimized display persistence time period is a shorter display persistence time period selected from the first display persistence time period and the second display persistence time period. 9. The method of claim 7 , wherein the optimized display persistence time period is a weighted average of the first display persistence time period and the second display persistence time period. 10. The method of claim 7 , further comprising determining a gazing point of the user on the display, wherein the optimized display persistence time period is determined further based on the gazing point of the user on the display. 11. The method of claim 7 , further comprising: determining a third display persistence time period for the image based on a spatial frequency of the content of the image, wherein the optimized display persistence time is determined based on the first display persistence time period, the second persistence display time period, and the third display persistence time period. 12. The method of claim 11 , wherein the optimized display persistence time period is a weighted average of the first display persistence time period, the second display persistence time period, and the third display persistence time period. 13. The method of claim 11 , wherein the optimized display persistence time period is a shortest display persistence time period selected from the first display persistence time period, the second display persistence time period, and the third display persistence time period. 14. The method of claim 1 , further comprising: determining one or more second characteristics associated with the content of the image, wherein the one or more second characteristics comprise a temporal frequency in a temporal frequency domain; and determining a frame rate for the image based on the one or more second characteristics associated with the content of the image, wherein the display is configured to display the image using the frame rate. 15. The method of claim 14 , wherein the frame rate is determined based on the one or more first characteristics comprising the contrast level of the content of the image with respect to the background of the image and the one or more second characteristics comprising the temporal frequency in the temporal frequency domain. 16. The method of claim 1 , wherein the first display persistence time period is determined based on a time period threshold to avoid flicker artifacts, and wherein the first display persistence time period is longer than the time period threshold. 17. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: access an image to be displayed by a display; determine one or more first characteristics associated with a content of the image, wherein the one or more first characteristics comprise a contrast level of the content of the image with respect to a background of the image, and wherein the contrast level is determined based on pixel values associated with the content of the image and (1) pixel values associated with a background portion of the image or (2) a brightness level associated with a real-world scene; determine a first display persistence time period for the display to display the image based on the one or more first characteristics associated with the content of the image; and configure the display to display the image using the first display persistence time period. 18. The media of claim 17 , further embodying software that is operable when executed to determine, using a prediction model, a likelihood level of the image to have visible motion blur when displayed by the display. 19. A system comprising: one or more processors; and one or more computer-readable non-transitory storage media coupled to one or more of the processors and comprising instructions operable when executed by one or more of the processors to cause the system to: access an image to be displayed by a display; determine one or more first characteristics associated with a content of the image, wherein the one or more first characteristics comprise a contrast level of the content of the image with respect to a background of the image, and wherein the contrast level is determined based on pixel values associated with the content of the image and (1) pixel values associated with a background portion of the image or (2) a brightness level associated with a real-world scene; determine a first display persistence time period for the display to display the image based on the one or more first characteristics associated with the content of the image; and configure the display to display the image using the first display persistence time period. 20. The system of claim 19 , further being configured to determine, using a prediction model, a likelihood level of the image to have visible motion blur when displayed by the display.
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