David Paul Mckinnon

US Patent:

20120163672, Jun 28, 2012

Filed:

Dec 20, 2011

Appl. No.:

13/330883

Inventors:

David McKinnon - Los Angeles CA, US

International Classification:

G06K 9/00

US Classification:

382106

Abstract:

Systems and methods for generating pixel based depth estimates are disclosed. An image processing system operating as depth analysis engine generates an estimated depth associated with a pixel based on a reference image and other related images. A current depth estimate is refined based on neighboring pixels and calculated consistency scores. Further, depth estimates can be levered in object or scene recognition to trigger or initiate an action taken by a computing device.

US Patent:

20200301502, Sep 24, 2020

Filed:

Jun 11, 2020

Appl. No.:

16/899518

Inventors:

- Culver City CA, US
John Wiacek - Culver City CA, US
David McKinnon - Culver City CA, US
Matheen Siddiqui - Culver City CA, US

Assignee:

Nant Holdings IP, LLC - Culver City CA

International Classification:

G06F 3/01
H04L 29/06
G06F 3/0484
G06F 3/0481
A63F 13/65
A63F 13/213
G06T 19/00
A63F 13/215

Abstract:

Multiparty object recognition systems and methods are disclosed. A method of interactively manipulating virtual object data, wherein an object database is configured to store first party object data that corresponds to a first real-world object and is further configured to store second party object data that corresponds to a second real-world object, includes obtaining the first party object data and the second party object data for storage within the object database. Access to the object database is controlled such that the first party object data and the second party object data is accessible to the first party and the second party. Modification of the first party object data by the second party is facilitated to generate modified first party object data that is in accordance with at least one context parameter of the second party object data, and the modified first party object data is communicated to the first party.

US Patent:

20180189608, Jul 5, 2018

Filed:

Feb 27, 2018

Appl. No.:

15/907130

Inventors:

- Culver City CA, US
David McKinnon - Culver City CA, US

Assignee:

Nant Holdings IP, LLC - Culver City CA

International Classification:

G06K 9/62
G06F 17/27
G06F 17/30

Abstract:

Systems and methods of generating a compact visual vocabulary are provided. Descriptor sets related to digital representations of objects are obtained, clustered and partitioned into cells of a descriptor space, and a representative descriptor and index are associated with each cell. Generated visual vocabularies could be stored in client-side devices and used to obtain content information related to objects of interest that are captured.

US Patent:

20180165519, Jun 14, 2018

Filed:

Jan 26, 2018

Appl. No.:

15/881043

Inventors:

- Culver City CA, US
Bing Song - La Canada CA, US
Matheen Siddiqui - Culver City CA, US
David McKinnon - Venice CA, US
Jeremi Sudol - Los Angeles CA, US
Patrick Soon-Shiong - Los Angeles CA, US
Orang Dialameh - Santa Monica CA, US

Assignee:

Nant Holdings IP, LLC - Culver City CA

International Classification:

G06K 9/00
G06T 7/00
G06F 17/30
G06T 11/60
G16H 30/40
G06K 9/62

Abstract:

Systems and methods of quickly recognizing or differentiating many objects are presented. Contemplated systems include an object model database storing recognition models associated with known modeled objects. The object identifiers can be indexed in the object model database based on recognition features derived from key frames of the modeled object. Such objects are recognized by a recognition engine at a later time. The recognition engine can construct a recognition strategy based on a current context where the recognition strategy includes rules for executing one or more recognition algorithms on a digital representation of a scene. The recognition engine can recognize an object from the object model database, and then attempt to identify key frame bundles that are contextually relevant, which can then be used to track the object or to query a content database for content information.

US Patent:

20180005081, Jan 4, 2018

Filed:

Sep 15, 2017

Appl. No.:

15/706600

Inventors:

- Culver City CA, US
Jeremi Sudol - Los Angeles CA, US
Bing Song - La Canada CA, US
Matheen Siddiqui - Culver City CA, US
David McKinnon - Culver City CA, US

Assignee:

Nant Holdings IP, LLC - Culver City CA

International Classification:

G06K 9/62
G06K 9/46

Abstract:

A sensor data processing system and method is described. Contemplated systems and methods derive a first recognition trait of an object from a first data set that represents the object in a first environmental state. A second recognition trait of the object is then derived from a second data set that represents the object in a second environmental state. The sensor data processing systems and methods then identifies a mapping of elements of the first and second recognition traits in a new representation space. The mapping of elements satisfies a variance criterion for corresponding elements, which allows the mapping to be used for object recognition. The sensor data processing systems and methods described herein provide new object recognition techniques that are computationally efficient and can be performed in real-time by the mobile phone technology that is currently available.

US Patent:

20170262704, Sep 14, 2017

Filed:

May 22, 2017

Appl. No.:

15/602022

Inventors:

- Culver City CA, US
Bing Song - La Canada CA, US
Matheen Siddiqui - Culver City CA, US
David McKinnon - Venice CA, US
Jeremi Sudol - Los Angeles CA, US
Patrick Soon-Shiong - Los Angeles CA, US
Orang Dialameh - Santa Monica CA, US

Assignee:

Nant Holdings IP, LLC - Culver City CA

International Classification:

G06K 9/00
G06T 7/00
G06K 9/62
G06T 11/60
G06F 17/30
G06F 19/00

Abstract:

Systems and methods of quickly recognizing or differentiating many objects are presented. Contemplated systems include an object model database storing recognition models associated with known modeled objects. The object identifiers can be indexed in the object model database based on recognition features derived from key frames of the modeled object. Such objects are recognized by a recognition engine at a later time. The recognition engine can construct a recognition strategy based on a current context where the recognition strategy includes rules for executing one or more recognition algorithms on a digital representation of a scene. The recognition engine can recognize an object from the object model database, and then attempt to identify key frame bundles that are contextually relevant, which can then be used to track the object or to query a content database for content information.

US Patent:

20170046571, Feb 16, 2017

Filed:

Oct 27, 2016

Appl. No.:

15/336754

Inventors:

- Culver City CA, US
Bing Song - La Canada CA, US
Matheen Siddiqui - Culver City CA, US
David McKinnon - Venice CA, US
Jeremi Sudol - Los Angeles CA, US
Patrick Soon-Shiong - Los Angeles CA, US
Orang Dialameh - Santa Monica CA, US

Assignee:

Nant Holdings IP, LLC - Culver City CA

International Classification:

G06K 9/00
G06T 11/60

Abstract:

Systems and methods of quickly recognizing or differentiating many objects are presented. Contemplated systems include an object model database storing recognition models associated with known modeled objects. The object identifiers can be indexed in the object model database based on recognition features derived from key frames of the modeled object. Such objects are recognized by a recognition engine at a later time. The recognition engine can construct a recognition strategy based on a current context where the recognition strategy includes rules for executing one or more recognition algorithms on a digital representation of a scene. The recognition engine can recognize an object from the object model database, and then attempt to identify key frame bundles that are contextually relevant, which can then be used to track the object or to query a content database for content information.

US Patent:

20170039442, Feb 9, 2017

Filed:

Oct 18, 2016

Appl. No.:

15/297053

Inventors:

- Culver City CA, US
David McKinnon - Venice CA, US
Jeremi Sudol - Los Angeles CA, US
Bing Song - La Canada CA, US
Matheen Siddiqui - Culver City CA, US

Assignee:

Nant Holdings IP, LLC - Culver City CA

International Classification:

G06K 9/32
G06F 17/30
G06K 9/00
G06K 9/46
G06T 7/00
G06T 7/60

Abstract:

An object recognition ingestion system is presented. The object ingestion system captures image data of objects, possibly in an uncontrolled setting. The image data is analyzed to determine if one or more a priori know canonical shape objects match the object represented in the image data. The canonical shape object also includes one or more reference PoVs indicating perspectives from which to analyze objects having the corresponding shape. An object ingestion engine combines the canonical shape object along with the image data to create a model of the object. The engine generates a desirable set of model PoVs from the reference PoVs, and then generates recognition descriptors from each of the model PoVs. The descriptors, image data, model PoVs, or other contextually relevant information are combined into key frame bundles having sufficient information to allow other computing devices to recognize the object at a later time.