IP Library Patent Application 15891329
Patent Application
App. No. 15/891,329

AUTOMATED VISUAL INFORMATION CONTEXT AND MEANING COMPREHENSION SYSTEM

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 None
App. No.
15/891,329
Abstract

A system for analyzing images and video that is capable of recognizing, classifying, and processing the context and meaning contained therein in a manner similar to human intuitive understanding of such context and meaning. Images and video are gathered through a crowdsourcing portal, fixed cameras, and other remote sensing devices. Real world data relevant to the images and video is gathered using a deep web extraction engine. The resulting inputs are analyzed for context and meaning using machine learning algorithms, whose outputs and reviewed and adjusted by humans through a crowdsourcing portal.

Claims (18)

1 . A system for analysis of images and video that is capable of recognizing, classifying, and processing the context and meaning contained therein in a manner similar to human intuitive understanding of such context and meaning, comprising:

an algorithm database comprising a multiplicity of algorithms for the processing and analysis of images and video; and

a crowdsourcing portal comprising at least a processor, a memory, and a plurality of programming instructions stored in the memory and operating on the processor, wherein the programming instructions, when operating on the processor, cause the processor to:

allow the collectivization of data gathering from a multiplicity of sources as input to the scene comprehension engine; and

allow individuals and groups to review and correct the context and meaning generated by the scene comprehension engine for images and video; and

a deep web extraction engine comprising at least a processor, a memory, and a plurality of programming instructions stored in the memory and operating on the processor, wherein the programming instructions, when operating on the processor, cause the processor to:

gather data from a multiplicity of sources on the internet for use by the scene comprehension engine in analyzing images and video; and

a scene comprehension engine comprising at least a processor, a memory, and a plurality of programming instructions stored in the memory and operating on the processor, wherein the programming instructions, when operating on the processor, cause the processor to:

receive images and video from a multiplicity of sources, including at least the crowdsourcing portal;

receive real world data from a multiplicity of sources, including at least the deep web extraction engine, relevant to comprehension of the context and meaning contained within the images and video;

obtain and utilize image and video processing algorithms from the algorithm database; and

analyze the images and video using at least one machine learning algorithm designed to identify the context and meaning contained in the images and video.

2 . A method for analysis of images and video that is capable of recognizing, classifying, and processing the context and meaning contained therein in a manner similar to human intuitive understanding of such context and meaning, comprising the steps of:

(a) obtaining images and video from a multiplicity of sources, including at least a crowdsourcing portal;

(b) gathering real world data from a multiplicity of sources, including at least a deep web extraction engine, relevant to comprehension of the context and meaning contained within the images and video;

(c) obtaining and utilizing image and video processing algorithms from an algorithm database;

(d) analyzing the images and video using at least one machine learning algorithm designed to identify the context and meaning contained in the images and video; and

(e) allowing individuals and groups to review and correct the context and meaning generated by the machine learning algorithm for images and video.

Assignments (8)
CHANGE OF ADDRESS Recorded Oct 1, 2024
From: QOMPLX LLC
To: QOMPLX LLC
Reel/Frame 069083/0279 →
CHANGE OF NAME Recorded Sep 27, 2023
From: QPX LLC
To: QOMPLX LLC
Reel/Frame 065036/0449 →
CORRECTIVE ASSIGNMENT TO CORRECT THE RECEIVING PARTY PREVIOUSLY RECORDED AT REEL: 064674 FRAME: 0408. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Sep 20, 2023
From: QOMPLX, INC.
To: QPX LLC
Reel/Frame 064966/0863 →
PATENT ASSIGNMENT AGREEMENT TO ASSET PURCHASE AGREEMENT Recorded Aug 23, 2023
From: QOMPLX, INC.
To: QPX, LLC.
Reel/Frame 064674/0407 →
CHANGE OF ADDRESS Recorded Oct 27, 2020
From: QOMPLX, INC.
To: QOMPLX, INC.
Reel/Frame 054298/0094 →
CHANGE OF NAME Recorded Aug 7, 2019
From: FRACTAL INDUSTRIES, INC.
To: QOMPLX, INC.
Reel/Frame 049996/0698 →
CHANGE OF ADDRESS Recorded Aug 7, 2019
From: FRACTAL INDUSTRIES, INC.
To: QOMPLX, INC.
Reel/Frame 049996/0683 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 8, 2018
From: CRABTREE, JASON; SELLERS, ANDREW
To: FRACTAL INDUSTRIES, INC.
Reel/Frame 044875/0694 →