Interference damping for continuous game play

• US 10,486,061 B2
• Filed: 11/28/2016
• Issued: 11/26/2019
• Est. Priority Date: 03/25/2016
• Status: Active Grant

• Current Assignee: Zero Latency Pty., Ltd.
• Original Assignee: Zero Latency Pty., Ltd.
• Inventors: Vandonkelaar, Scott
• Primary Examiner(s): Spinks, Antoinette T
• Application Number:
  US15/362,611
• Publication Number:
  US 20170274275A1
• Time in Patent Office: 1,093 Days
• Field of Search: 34821111
• CPC Class Codes: A63F 13/212 using sensors worn by the player, e.g. for measuring heart beat or leg activity
• CPC Class Codes: A63F 13/213 comprising photodetecting means, e.g. cameras, photodiodes or infrared cells A63F13/219, A63F13/655 take precedence
• CPC Class Codes: A63F 13/35 Details of game servers
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 2207/30204 Marker
• CPC Class Codes: G06T 2207/30212 Military
• CPC Class Codes: G06T 2207/30241 Trajectory
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06T 7/292 Multi-camera tracking
• CPC Class Codes: G06V 10/245 by locating a pattern; Special marks for positioning
• CPC Class Codes: G06V 10/62 relating to a temporal dimension, e.g. time-based feature extraction; Pattern tracking
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: H04N 17/002 for television cameras
• CPC Class Codes: H04N 23/66 Remote control of cameras or camera parts, e.g. by remote control devices
• CPC Class Codes: H04N 23/90 Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums
• CPC Class Codes: H04N 5/2224 related to virtual studio applications

Abstract

Within a system for operating a virtual reality game or environment, a method is provided for identification of problematic or not well calibrated cameras that are incapable of optimum identification and tracking of game objects. The impact of these identified cameras on the game is reduced on the fly. Most of the time, a few cameras will see an object. The images are mixed to identify the object and its location according to vectors established between cameras and trackable objects. When such mixing of images happens, identification of non-optimum non-calibrated cameras is enabled and performed. The impact of such cameras is then reduced in the overall impact in the game play, providing higher emphasis to images from well calibrated cameras. As such, game stoppage and re-calibration of these few cameras is not required for continuous game play.

Claims

1. A computerized method wherein one or more processors determine a position of an object in a virtual reality environment while de-emphasizing cameras having less than optimum positioning accuracy, the method comprising:

locating an object in images received from two or more cameras;

determining one or more intersections of vectors, wherein each vector originates at a camera and passes near the object;

establishing a system-wide tracking error margin that represents the maximum allowable error for any detected intersection;

initializing an object position vector for the object and a total position weight for the object;

for a first intersection formed between a pair of vectors, performing the steps of;

(a) identifying an intersect error margin for the intersection that comprises the closest distance between the pair of vectors;

(b) computing a weight by subtracting the intersect error margin from the tracking error margin and dividing the result by the tracking error margin;

(c) determining a position for the intersection based on the pair of intersecting vectors; and

(d) multiplying the position by the weight, and adding the product to the object position vector to produce a revised object position vector;

(e) adding the weight to the total position weight; and

dividing the revised object position vector by the total position weight to produce a final position for the object.

2. The method of claim 1, further comprising:

repeating steps (a) through (e) for a second intersection formed between a pair of vectors.

3. The method of claim 1, further comprising:

locating a plurality of objects with the two or more cameras, and repeating all of the steps for each of the plurality of objects.

4. A system for determining a position of an object in a virtual reality environment while de-emphasizing cameras having less than optimum positioning accuracy, the system comprising:

a processor;

a memory containing machine readable medium comprising machine executable code having stored thereon instructions for operating the system, wherein the processor is coupled to the memory, wherein the system is configured to execute the machine executable code to cause the control system to;

locate an object in images received from two or more cameras;

determine one or more intersections of vectors, wherein each vector originates at a camera and passes near the object;

establish a system-wide tracking error margin that represents the maximum allowable error for any detected intersection;

initialize an object position vector for the object and a total position weight for the object;

for a first intersection formed between a pair of vectors, perform the steps of;

(a) identify an intersect error margin for the intersection that comprises the closest distance between the pair of vectors;

(b) compute a weight by subtracting the intersect error margin from the tracking error margin and dividing the result by the tracking error margin;

(c) determine a position for the intersection based on the pair of intersecting vectors; and

(d) multiply the position by the weight, and adding the product to the object position vector to produce a revised object position vector;

(e) add the weight to the total position weight; and

divide the revised object position vector by the total position weight to produce a final position for the object.

5. The system of claim 4, wherein the system is configured to execute the machine executable code to further cause the control system to:

repeat steps (a) through (e) for a second intersection formed between a pair of vectors.

6. The system of claim 4, wherein the system is configured to execute the machine executable code to further cause the control system to:

locate a plurality of objects with the two or more cameras, and repeat all of the steps for each of the plurality of objects.