Detecting content in a real-time video stream using machine-learning classifiers

US11823442B2 · kind B2 · utility

Assignee

• MATROID, INC. · US

Inventors

• Reza Zadeh · Emerald Hills, US
• Ryan Wong · Palo Alto, US
• John Goddard · Mountain View, US
• Jiahang Li · Palo Alto, US
• Steven Chen · San Francisco, US
• Xiaoyun Yang · Zhaoyuan, CN

Key dates

• Filing date: Mar 4, 2020
• Grant date: Nov 21, 2023
• Expiry date: Aug 17, 2040

Classification

• Technology area (CPC G): Physics
• CPC primary: G06V20/49
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Described herein are systems and methods that search videos and other media content to identify items, objects, faces, or other entities within the media content. Detectors identify objects within media content by, for instance, detecting a predetermined set of visual features corresponding to the objects. Detectors configured to identify an object can be trained using a machine learned model (e.g., a convolutional neural network) as applied to a set of example media content items that include the object. The systems and methods describe techniques that search videos and media content to determine the presence of unknown objects, generate novel detectors trained to identify the unknown objects, and apply the novel detectors to historical media content to identify previous appearances of the unknown objects.