Interaction Detection Model for Identifying Human-Object Interactions in Image Content

Patent №

US 11,106,902

Granted

2021-08-31

Filed 2018

Owner

ADOBE SYSTEMS INCORPORATED

Lab

AI components

5

ml · nlp · vision · kr · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

15920027

Certain embodiments detect human-object interactions in image content. For example, human-object interaction metadata is applied to an input image, thereby identifying contact between a part of a depicted human and a part of a depicted object. Applying the human-object interaction metadata involves computing a joint-location heat map by applying a pose estimation subnet to the input image and a contact-point heat map by applying an object contact subnet to the to the input image. The human-object interaction metadata is generated by applying an interaction-detection subnet to the joint-location heat map and the contact-point heat map. The interaction-detection subnet is trained to identify an interaction based on joint-object contact pairs, where a joint-object contact pair includes a relationship between a human joint location and a contact point. An image search system or other computing system is provided with access to the input image having the human-object interaction metadata.

Machine learningNatural languageVisionKnowledge representationAI hardwareG06N 3/08G06V 10/82G06N 3/045G06N 3/0464G06N 3/09G06N 3/091G06N 5/046G06T 7/70+4 more

AI classification

Vision1.00
Machine learning1.00
AI hardware1.00
Knowledge representation0.99
Natural language0.62
Planning0.29
Evolutionary computation0.04
Speech0.00

Ownership

ADOBE SYSTEMS INCORPORATED

assignment · 451920049

Assignors

KIM, VLADIMIR, YUMER, MEHMET ERSIN, LI, ZIMO

On an employer assignment, the assignors are typically the inventors.

From the same owner

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