Apple Xris – Video Patents From Korean Research Entity

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Patent Portfolio Acquisition

Patents are a significant financial investment for any company. It is also an excellent approach to generate revenue if you have a small or new business. The company can monetize the patents in a variety of ways, including selling or licensing the patents to other companies if the patent owner company lacks the resources to manufacture or market their own product, or just does not want to.

The Patent Portfolio Acquisition allows firm A to purchase IP from company B that overlaps. As a result, the portfolio of company A portfolio becomes stronger, and the chances of infringement are reduced.

The Apple and XRIS corporate dealings are the most recent addition to this group, with Apple purchasing 14 XRIS US patents for an undisclosed sum. All of the patents were filed by the same inventor, Bae Keun Lee, and are linked to XRIS’ video technology portfolio. The XRIS Corporation has a powerful video technology portfolio.

It is also recognized as a licensor in the VVC advance patent pool. This is a patent pool that Access Advance LLC manages and administers (formerly known as HEVC Advance). Access Advance acts as a bridge between patent owners and patent implementers by providing a license to a pool of patents. Apple’s patent portfolio will be strengthened by the acquisitions, and some of the patents may be SEPs because XRIS is a member of H.266 standards committees (V2). Apple will gain financially as a result of patent licensing Interesting, Apple already has approx. 6% of its Patent Portfolio in this domain. Majorly the technology disclosed in the XRIS’s patents acquired by Apple is related to encoding and decoding of image or video signals. The patents are disclosing different ways of making encoding and decoding efficient and fast. Some of the ways described in the patents are as follows:

  • The invention involves a method of determining whether a picture is divided into a number of subpictures. A determination is made whether the number of sub-pictures are provided with independence based on a first flag. The first flag is provided to indicate that the number of subpictures are not provided independence. A first flag is provided for indicating whether each subpicture has independence. The number of subpictures are determined in the picture. Location information and size information is determined for each of the subpictures. The signaled position information is omitted for the first sub-picture among the sub-pictures.
  • The invention involves parsing a first flag indicating whether inter prediction based on the current block edge mode is applied and when the first flag is true, a step of parsing a second flag is carried out indicating whether a regular merge mode or a merge offset encoding mode is applied to the current block. The step of parsing a third flag indicating whether or not the merge offset encoding mode is applied is included, but if the third flag is true, the merge offset encoding mode is applied to the current block, and the third flag is false. Method for encoding and decoding a video signal. The method helps to improve the video compression rate that is actively being conducted. 
  • The method disclosed in the invention involves generating an affine merge candidate list for the current block. The affine merge candidates included in the affine merge candidate list are specified. The affine seed vectors of the specified merge candidate are derived. A sub-block motion vector is derived for a sub-block in the current block using the affine seed vectors. The sub-block is an area smaller than the current block. The offset data is derived for the sub-blocks. A sub prediction block is generated for the sub-block based on the affine vector and the offset data. A flag is decoded for determining whether to use the offset data through a bitstream.
Graphical Analysis of XRIS Corporation

Note: The graphical analysis shown below is based on the 188 patent publications of XRIS corporation.

  • Portfolio Summary Analyze the breakdown of types of patent publications in the portfolio as well as the current legal status. This helps to identify the patent publications that are alive or dead and also indicates the legal state.

Note: Innermost pie: Shows the publication type. Second level pie: Shows the simple legal status for the publications. Third level pie: Shows the current legal state corresponding to the simple legal status for the publications.

Insight: The total patent set of XRIS corporation is 188. Out of 188, 184 are applications and 4 are granted patents. Maximum patents are in the publication stage.

  • Patent Trend This chart shows the number of applications filed and the number of grants from these applications. Grant rate is a good indicator to identify successful applications and the graph helps to understand the progress in the technology area. For the Application Year trend, the granted patents are shown in the year in which their corresponding applications were filed. For example: if a 2015 patent application is granted in 2018, the granted patent will appear in 2015. Note: The chart is prepared on one member per application family dataset.

Application Year

Some Competitors of XRIS Corp

How can TT Consultants help you? First, let’s address why a company would be interested in buying or selling a patent portfolio? There are a variety of reasons for which a company might be interested in buying or selling a patent portfolio :

  • The technical domain overlaps and the company can strengthen its portfolio by acquiring patents.
  • The company’s products infringe on patents.
  • Patents are so broad that they can be utilized for monetary gain through licensing or infringement.
  • The patents are SEPs (standard essential patents).

TT Consultants can assist you in determining whether to buy or sell a patent portfolio. We can discover patents that you can sell to generate revenue or patents from other companies with overlapping domains that you can buy by browsing through the portfolio.

We offer a reliable strategy that combines AI and the human touch. Click here to down the full report.

Author
Yogesh Nayak
 
About TTC
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