IP Library › Granted Patent US 12,458,884
Granted Patent B2
US 12,458,884 · App. 17/203,958 · Granted Nov 4, 2025

Object viewability determination system and method

Inventor: Michael Badichi (Tel Aviv, IL)
Assignee: Anzu Virtual Reality LTD.
A63F13/53A63F13/46A63F13/61G06Q30/02G06Q30/0242
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,458,884
App. No.
17/203,958
Granted
Nov 4, 2025
Kind
B2
Abstract

A system for calculating viewability scores of objects displayed within a viewport, the system comprising a processing resource configured to perform the following for at least one object of the objects: determine a first value indicative of a relative portion of the object from the viewport; and calculate a viewability score of the object, wherein the viewability score is calculated based on the first value.

Claims (33)

1 . A system for determining viewability of an object displayed within a scene, the system comprising one or more processing units configured to:

divide said object displayed within said scene into a plurality of segments, each composed of a plurality of pixels;

for each segment of said plurality of segments, determine an average color value based on color encoding values of the pixels within the segment;

identify one or more segments having a dominating desired color, wherein a segment is determined to have a dominating desired color if the color encoding values of the pixels in the segment are within a threshold distance from the average color value of that segment;

determine an actual color for each of the segments having a dominating desired color, based on visual data of the object as displayed in a rendered scene;

compare, for each segment having a dominating desired color, the actual color of the segment to a corresponding desired color to generate a color resemblance value; and,

based on the color resemblance values of the dominating color segments, calculate a viewability score of the object, being indicative of the object's visibility within said scene.

2 . The system of claim 1 , wherein upon the color resemblance value being lower than a low threshold, the viewability score is calculated based on an under-threshold-value indicative of the color resemblance value being under the low threshold.

3 . The system of claim 2 , wherein the under-threshold-value is zero.

4 . The system of claim 1 , wherein upon the color resemblance value being higher than a high threshold, the viewability score is calculated based on an over-threshold-value indicative of the color resemblance value being over the high threshold.

5 . The system of claim 4 , wherein the over-threshold-value is one.

6 . The system of claim 1 , wherein the processing resource is further configured to determine a second value indicative of a relative portion of the object from the viewport, and wherein the viewability score is calculated also based on the second value.

7 . The system of claim 1 , wherein the processing resource is further configured to determine a third value indicative of relative portion of the object visible in the viewport, and wherein the viewability score is calculated also based on the third value.

8 . A method for determining viewability of an object displayed within a scene, the method comprising:

dividing said object displayed within said scene into a plurality of segments, each composed of a plurality of pixels;

for each segment of said plurality of segments, determining an average color value based on color encoding values of the pixels within the segment;

identifying one or more segments having a dominating desired color, wherein a segment is determined to have a dominating desired color if the color encoding values of the pixels in the segment are within a threshold distance from the average color value of that segment;

determining an actual color for each of the segments having a dominating desired color, based on visual data of the object as displayed in a rendered scene;

comparing, for each segment having a dominating desired color, the actual color of the segment to a corresponding desired color to generate a color resemblance value; and,

based on the color resemblance values of the dominating color segments, calculating a viewability score of the object, being indicative of the object's visibility within said scene.

9 . The method of claim 8 , wherein upon the color resemblance value being lower than a low threshold, the viewability score is calculated based on an under-threshold-value indicative of the color resemblance value being under the low threshold.

10 . The method of claim 9 , wherein the under-threshold-value is zero.

11 . The method of claim 8 , wherein upon the color resemblance value being higher than a high threshold, the viewability score is calculated based on an over-threshold-value indicative of the color resemblance value being over the high threshold.

12 . The method of claim 11 , wherein the over-threshold-value is one.

13 . The method of claim 8 , further comprising determining, by the processing resource, a second value indicative of a relative portion of the object from the viewport, and wherein the viewability score is calculated also based on the second value.

14 . The method of claim 8 , further comprising determining, by the processing resource, a third value indicative of relative portion of the object visible in the viewport, and wherein the viewability score is calculated also based on the third value.

15 . A non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, executable by at least one processing resource of a computer to perform a method for determining viewability of an object displayed within a scene, the method comprising performing the following:

dividing said object displayed within said scene into a plurality of segments, each composed of a plurality of pixels;

for each segment of said plurality of segments, determining an average color value based on color encoding values of the pixels within the segment;

identifying one or more segments having a dominating desired color, wherein a segment is determined to have a dominating desired color if the color encoding values of the pixels in the segment are within a threshold distance from the average color value of that segment;

determining an actual color for each of the segments having a dominating desired color, based on visual data of the object as displayed in a rendered scene;

comparing, for each segment having a dominating desired color, the actual color of the segment to a corresponding desired color to generate a color resemblance value; and,

based on the color resemblance values of the dominating color segments, calculating a viewability score of the object, being indicative of the object's visibility within said scene.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 17, 2021
From: BADICHI, MICHAEL
To: ANZU VIRTUAL REALITY LTD.
Reel/Frame 055619/0157 →
Continuity (4)
Continuation 16765907
Provisional Application 62619827 · Jan 21, 2018
Related Publication 20210205704A1 · Jul 8, 2021
Related Publication 20250073583A2 · Mar 6, 2025
References Cited (40)
US 8751310B2 · van Datta et al. · 2014 [cited by applicant]
US 9180369B2 · Willis et al. · 2015 [cited by applicant]
US 10783548B1 · Bhowmick · 2020 [cited by examiner]
US 20030187730A1 · Natarajan · 2003 [cited by applicant]
US 20070025624A1 · Baumberg · 2007 [cited by applicant]
US 20070242162A1 · Gutta · 2007 [cited by examiner]
US 20080102947A1 · Hays · 2008 [cited by examiner]
US 20090219300A1 · Peleg et al. · 2009 [cited by applicant]
US 20100100429A1 · McCloskey et al. · 2010 [cited by applicant]
US 20100182340A1 · Bachelder · 2010 [cited by examiner]
US 20100217666A1 · Belenguer · 2010 [cited by examiner]
US 20100278421A1 · Peters · 2010 [cited by examiner]
US 20110115883A1 · Kellerman · 2011 [cited by examiner]
US 20110157410A1 · Alcazar · 2011 [cited by examiner]
US 20110319160A1 · Arn · 2011 [cited by examiner]
US 20120314086A1 · Hubel et al. · 2012 [cited by applicant]
US 20130185164A1 · Pottjegort · 2013 [cited by applicant]
US 20140037200A1 · Phillips · 2014 [cited by examiner]
US 20140195330A1 · Lee et al. · 2014 [cited by applicant]
US 20140229268A1 · Clapp · 2014 [cited by applicant]
US 20140375645A1 · Bakalash · 2014 [cited by applicant]
US 20150110340A1 · Harron · 2015 [cited by examiner]
US 20160148433A1 · Petrovskaya · 2016 [cited by examiner]
US 20160171954A1 · Guo · 2016 [cited by examiner]
US 20160191815A1 · Annau · 2016 [cited by examiner]
US 20160352971A1 · Kanematsu · 2016 [cited by examiner]
US 20170103572A1 · Lin et al. · 2017 [cited by applicant]
US 20170199888A1 · Toksoz et al. · 2017 [cited by applicant]
US 20170359570A1 · Holzer · 2017 [cited by examiner]
US 20170372380A1 · Candiotti · 2017 [cited by examiner]
US 20170372389A1 · Busch · 2017 [cited by examiner]
US 20180012378A1 · Khandpur · 2018 [cited by applicant]
US 20190012681A1 · Guo · 2019 [cited by examiner]
US 20190244416A1 · Tamaoki · 2019 [cited by examiner]
US 20190306434A1 · Annau · 2019 [cited by examiner]
US 20200110262A1 · Bakos · 2020 [cited by examiner]
US 20200394453A1 · Ma · 2020 [cited by examiner]
US 20210193085A1 · Haas · 2021 [cited by examiner]
WO 2008001472 · 2008 [cited by applicant]
WO WO2018067731A1 · 2017 [cited by examiner]