18065074. ATTENTION MONITORING IN A VIDEO CONFERENCING SESSION simplified abstract (Capital One Services, LLC)

ATTENTION MONITORING IN A VIDEO CONFERENCING SESSION

Organization Name

Capital One Services, LLC

Inventor(s)

Vamsi Kavuri of Glen Allen VA (US)

Jignesh Rangwala of Glen Allen VA (US)

Lee Adcock of Midlothian VA (US)

Mehulkumar Jayantilal Garnara of Glen Allen VA (US)

ATTENTION MONITORING IN A VIDEO CONFERENCING SESSION - A simplified explanation of the abstract

This abstract first appeared for US patent application 18065074 titled 'ATTENTION MONITORING IN A VIDEO CONFERENCING SESSION

Simplified Explanation: The patent application describes a system that uses machine learning to analyze user attention data in a video conferencing session and identify non-attentive users to take corrective actions.

• Key Features and Innovation:

   * System receives user data from multiple devices in a video conferencing session.
   * Utilizes machine learning model trained on historical data to analyze user attention.
   * Identifies non-attentive users and takes actions to regain their attention.

• Potential Applications:

   * Remote learning platforms
   * Virtual team meetings
   * Online webinars

• Problems Solved:

   * Addressing lack of user engagement in video conferencing sessions
   * Improving overall participation and attentiveness in virtual meetings

• Benefits:

   * Enhanced user engagement
   * Improved communication and collaboration in virtual settings
   * Efficient use of meeting time

• Commercial Applications:

   * Virtual event platforms
   * Corporate video conferencing solutions
   * Educational technology companies

• Prior Art:

   Prior research on user engagement analysis in video conferencing sessions.

• Frequently Updated Research:

   Ongoing studies on user behavior analysis in virtual communication environments.

Questions about User Attention Analysis in Video Conferencing: 1. How does the system differentiate between attentive and non-attentive users? 2. What are the potential privacy concerns related to analyzing user attention data in video conferencing sessions?

Original Abstract Submitted

In some implementations, a system may receive user data from a plurality of user devices corresponding to a plurality of users participating in a video conferencing session. The system may provide, based on the user data and as input to a machine learning model, user attention data associated with attentions of the plurality of users with respect to the video conferencing session. The machine learning model may be trained based on historical user attention data associated with a plurality of historical video conferencing sessions. The system may receive, as output from the machine learning model, an indication that one or more non-attentive users, of the plurality of users, are not attentive to the video conferencing session. The system may perform, based on the indication, one or more actions to gain attention from the one or more non-attentive users.