View source for Intel corporation (20240194215). EQUALIZING AND TRACKING SPEAKER VOICES IN SPATIAL CONFERENCING simplified abstract

=EQUALIZING AND TRACKING SPEAKER VOICES IN SPATIAL CONFERENCING=


==Organization Name==

[[:Category:intel corporation|intel corporation]]


[[Category:intel corporation]]

==Inventor(s)==

[[:Category:Sumod Cherukkate of Bangalore (IN)|Sumod Cherukkate of Bangalore (IN)]][[Category:Sumod Cherukkate of Bangalore (IN)]]

[[:Category:Willem Beltman of West Linn OR (US)|Willem Beltman of West Linn OR (US)]][[Category:Willem Beltman of West Linn OR (US)]]

[[:Category:Mallari Hanchate of Bangalore (IN)|Mallari Hanchate of Bangalore (IN)]][[Category:Mallari Hanchate of Bangalore (IN)]]

[[:Category:Srikanth Potluri of Folsom CA (US)|Srikanth Potluri of Folsom CA (US)]][[Category:Srikanth Potluri of Folsom CA (US)]]

[[:Category:Sangeeta Manepalli of Chandler AZ (US)|Sangeeta Manepalli of Chandler AZ (US)]][[Category:Sangeeta Manepalli of Chandler AZ (US)]]

[[:Category:Abhishek Srivastav of Bangalore (IN)|Abhishek Srivastav of Bangalore (IN)]][[Category:Abhishek Srivastav of Bangalore (IN)]]

==EQUALIZING AND TRACKING SPEAKER VOICES IN SPATIAL CONFERENCING - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240194215 titled 'EQUALIZING AND TRACKING SPEAKER VOICES IN SPATIAL CONFERENCING

The patent application describes a system for user tracking using depth sensing and camera information from an in-room device to perform face recognition and calculate distances between users.

* The device identifies metadata from an in-room device with a camera and performs face recognition on users.
* It calculates the distance of users based on the metadata and the number of pixels across their faces.
* The system can determine the distance between multiple in-room users by analyzing the metadata and pixel data.

Potential Applications:
* Security systems for identifying and tracking individuals in a room.
* Interactive gaming experiences that adjust based on user proximity.
* Personalized advertising based on user demographics and behavior.

Problems Solved:
* Enhanced user tracking and identification in various applications.
* Improved security measures by accurately recognizing individuals in a room.
* Customized user experiences based on proximity and interactions.

Benefits:
* Increased accuracy in user tracking and identification.
* Enhanced security and privacy measures.
* Personalized and interactive user experiences.

Commercial Applications:
* Security companies could utilize this technology for access control and surveillance systems.
* Entertainment companies could integrate this system into interactive gaming experiences.
* Retailers could use this technology for targeted advertising and customer analytics.

Prior Art:
Prior art related to this technology may include patents or research on facial recognition systems, depth sensing technology, and user tracking methods.

Frequently Updated Research:
Ongoing research in the fields of computer vision, artificial intelligence, and human-computer interaction may provide new insights and advancements in user tracking technology.

Questions about User Tracking Technology:
1. How does this technology address privacy concerns related to user tracking?
2. What are the potential limitations of using depth sensing and camera information for user tracking?


==Original Abstract Submitted==

this disclosure describes systems, methods, and devices related to user tracking. a device may identify metadata comprising depth sensing information and camera information received from an in-room device located at a first location having a first camera. the device may perform face recognition on one or more in-room users. the device may calculate a distance of a first in-room user based on the metadata and a first number of pixels across the face of the first in-room user. the device may calculate a distance between the first in-room user and a second in-room user based on the metadata and the first number of pixels across the face of the first in-room user and a number of pixels across the face of the second in-room user.



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