Digital rights management for http-based media streaming
US-2023214459-A1 · Jul 6, 2023 · US
US11917124B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11917124-B2 |
| Application number | US-202217696423-A |
| Country | US |
| Kind code | B2 |
| Filing date | Mar 16, 2022 |
| Priority date | Nov 18, 2020 |
| Publication date | Feb 27, 2024 |
| Grant date | Feb 27, 2024 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
A display apparatus and a controlling method thereof are provided. The display apparatus includes a display comprising a first display panel, a lens array disposed on the first display panel, and a second display panel disposed on the lens array; and a processor to, based on a plurality of light field (LF) images, obtain a left (L) image and a right (R) image to drive the display by time-multiplexing, correct a second L image to drive the second display panel among the L images based on a first R image to drive the first display panel among the R images, and correct a second R image to drive the second display panel among the R images based on the first L image to drive the first display panel among the L images, and display a stereoscopic image by driving the display by time-multiplexing based on the L image which includes the corrected second L image and the R image which includes the corrected second R image. The display apparatus of the disclosure may use an artificial intelligence model trained according to at least one of a rule-based model, a machine learning, a neural network, or a deep learning algorithm.
Opening claim text (preview).
What is claimed is: 1. A display apparatus comprising: a display comprising: a first display panel comprising a plurality of sub-pixels, a lens array disposed on the first display panel and comprises a plurality of unit lens, and a second display panel disposed on the lens array; and a processor configured to: based on a plurality of light field (LF) images, obtain a left (L) image and a right (R) image to drive the display by time-multiplexing, correct a second L image to drive the second display panel among L images based on a first R image to drive the first display panel among R images, and correct a second R image to drive the second display panel among the R images based on a first L image to drive the first display panel among the L images, and display a stereoscopic image by driving the display by time-multiplexing based on the L image which comprises the corrected second L image and the R image which comprises the corrected second R image, wherein the lens array disposed on the first display panel such that respectively unit lens is arranged on a predetermined number of first sub-pixels, and wherein the processor is further configured to, based on information of a viewpoint at which a plurality of LF images are captured, extract an LF image representing a left viewpoint and an LF image representing a right viewpoint among the plurality of LF images, based on the LF image representing the left viewpoint obtain a left (L) images respectively corresponding to the first display panel and the second display panel, and based on the LF image representing the right viewpoint obtain a right (R) images respectively corresponding to the first display panel and the second display panel. 2. The display apparatus of claim 1 , wherein the processor is further configured to: obtain an R crosstalk image based on the first R image and an L crosstalk image based on the first L image; correct the second L image based on a pixel value of the R crosstalk image; and correct the second R image based on a pixel value of the L crosstalk image. 3. The display apparatus of claim 2 , wherein the processor is further configured to: correct the second L image to have a pixel value reduced as much as a pixel value of the R crosstalk image with respect to a pixel of a same position; and correct the second R image to have a pixel value reduced as much as a pixel value of the L crosstalk image with respect to a pixel of a same position. 4. The display apparatus of claim 2 , wherein the processor is further configured to: obtain the R crosstalk image having a pixel value obtained by multiplying a crosstalk ratio by the pixel value of the first R image; and obtain the L crosstalk image having a pixel value obtained by multiplying the crosstalk ratio by the pixel value of the first L image. 5. The display apparatus of claim 2 , wherein the processor is further configured to: obtain a third R image in which the first R image and the second R image are synthesized and obtain the R crosstalk image having a pixel value by multiplying a crosstalk ratio by the pixel value of the synthesized third R image; and obtain a third L image in which the first L image and the second L image are synthesized and obtain the L crosstalk image having a pixel value obtained by multiplying the crosstalk ratio by the pixel value of the synthesized third L image. 6. The display apparatus of claim 1 , wherein the processor is further configured to: obtain the L image by inputting the LF image representing the left viewpoint to a first factorization model trained to output the L image corresponding to a number of the first display panel and the second display panel; and obtain the R image by inputting the LF image representing the right viewpoint to a second factorization model trained to output the R image corresponding to a number of the first display panel and the second display panel. 7. The display apparatus of claim 6 , wherein the first factorization model is an artificial intelligence model trained until a loss function based on an LF image representing a left viewpoint and an LF image restored through the L image becomes less than or equal to a predetermined value, and wherein the second factorization model is an artificial intelligence model trained until a loss function based on an LF image representing a right point of view and an LF image restored through the R image becomes less than or equal to a predetermined value. 8. The display apparatus of claim 6 , wherein each of the first factorization model and the second factorization model is one of a deep neural network (DNN) model, a non-negative tensor factorization (NTF) model, or a non-negative matrix factorization (NMF) model. 9. The display apparatus of claim 1 , wherein the lens array comprises a unit lens disposed on an even number of sub-pixels of the first display panel. 10. The display apparatus of claim 1 , wherein the processor is further configured to: based on the LF image which are classified according to a viewpoint at which the plurality of LF images are captured, obtain the L image, an M image, and the R image corresponding to the viewpoint; correct the second L image based on a first M image and the first R image for driving the first display panel among the M images; correct the second R image based on the first M image and the first L image; based on the first L image and the first R image, correct a second M image for driving the second display panel among the M images; and display the stereoscopic image by driving the display by time-multiplexing based on the L image which comprises the corrected second L image, the M image which comprises the corrected second M image, and the R image which comprises the corrected second R image. 11. A controlling method of a display apparatus, the controlling method comprising: based on a plurality of light field (LF) images, obtaining a left (L) image and a right (R) image to drive a display comprising a first display panel comprising a plurality of sub-pixels, a lens array disposed on the first display panel, and a second display panel disposed on the lens array by time-multiplexing; correcting a second L image to drive the second display panel among L images based on a first R image to drive the first display panel among R images, and correct a second R image to drive the second display panel among the R images based on a first L image to drive the first display panel among the L images; and displaying a stereoscopic image by driving the display by time-multiplexing based on the L image which comprises the corrected second L image and the R image which comprises the corrected second R image, wherein the lens array comprises a plurality of unit lens and is disposed on the first display panel such that respectively unit lens is arranged on a predetermined number of first sub-pixels, and wherein the lens array disposed on the first display panel such that respectively unit lens is arranged on a predetermined number of the first sub-pixels, and wherein the obtaining a left (L) image and a right (R) image comprises: based on information of a viewpoint at which a plurality of LF images are captured, extracting an LF image representing a left viewpoint and an LF image representing a right viewpoint among the plurality of LF images, based on the LF image representing the left viewpoint obtaining a left (L) images respectively corresponding to the first display panel and the second display panel, and based on the LF image representing the right viewpoint obtaining a right (R) images respectively corresponding to the first display panel and the second display panel.
Supervised learning · CPC title
Feedforward networks · CPC title
involving lenticular arrays · CPC title
for crosstalk reduction · CPC title
Synchronisation thereof; Control thereof · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.