Invention Grant
- Patent Title: Training a neural network to track viewer engagement with non-interactive displays
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Application No.: US17084114Application Date: 2020-10-29
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Publication No.: US11308629B2Publication Date: 2022-04-19
- Inventor: Max Gray Edell , David E. Benge
- Applicant: ADOBE INC.
- Applicant Address: US CA San Jose
- Assignee: ADOBE INC.
- Current Assignee: ADOBE INC.
- Current Assignee Address: US CA San Jose
- Agency: Shook, Hardy & Bacon, L.L.P.
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G06T7/20 ; G06F3/01 ; G06N3/08 ; G06K9/00 ; G06N5/04

Abstract:
Methods and systems are provided for training a neural network to track viewer engagement with a non-interactive display. Sensor data is obtained from one or more sensors, such as cameras, associated with a display device, and once a face is detected within the sensor data, a display sequence is initiated. The display sequence includes at least a first frame with a first visual feature and a second frame with a second visual feature. Using the sensor data obtained during presentation of the display sequence, viewer engagement with the sequence is tracked by determining eye movements and/or head movements. The detected eye movement and/or head movement is used to determine whether the person was actively engaged with the display sequence.
Public/Granted literature
- US20210065378A1 TRAINING A NEURAL NETWORK TO TRACK VIEWER ENGAGEMENT WITH NON-INTERACTIVE DISPLAYS Public/Granted day:2021-03-04
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