Georgia Tech Research Corporation

Harish Kashyap Haresamudram

Gregory D Abowd

Thomas Ploetz

Nicholas Lane

Hyeokhyen Kwon

Eu Gen Catherine Tong

Yan Gao

An exemplary virtual IMU extraction system and method are disclosed for human activity recognition (HAR) or classifier system that can estimate inertial measurement units (IMU) of a person in video data extracted from public repositories of video data having weakly labeled video content. The exemplary virtual IMU extraction system and method of the human activity recognition (HAR) or classifier system employ an automated processing pipeline (also referred to herein as 'IMUTube') that integrates computer vision and signal processing operations to convert video data of human activity into virtual streams of IMU data that represents accelerometer, gyroscope, or other inertial measurement unit estimation that can measure acceleration, inertia, motion, orientation, force, velocity, etc. at a different location on the body. In other embodiments, the automated processing pipeline can be used to generate high-quality virtual accelerometer data from a camera sensor.

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Atlanta, GA, United States of America

Harish Kashyap Haresamudram