360-Degree Camera Participant Identification Beyond Invitee Lists
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Solution Overview
Problem
Conventional 360-degree video systems struggle to accurately identify participants in a meeting independently from an invitee list, leading to inefficiencies in user interaction and resource consumption.
Innovation Solution
Implementing a video conference device with a 360-degree camera and local identification-based performance logic to automatically identify participants using biometric techniques and wireless signal analysis, allowing for participant recognition without reliance on an invitee list, and enabling actions based on this identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional 360-degree video systems use invitee lists for participant identification, then participant identification can be performed, but user efficiency is reduced and time consumption increases
Solution Approach 1:
The system enables automatic participant identification through self-service mechanisms where the 360-degree camera captures images, the processor automatically processes these images to identify participants, and the system performs actions without requiring manual verification against invitee lists. This eliminates the need for users to manually check participant identities, thereby improving user efficiency and reducing time consumption.
2Measurement precision
If automatic participant identification is implemented independently from invitee lists, then identification accuracy improves, but system complexity increases
Solution Approach 1:
The patent replaces manual identification mechanisms (mechanical/systematic verification against invitee lists) with automated image processing and biometric recognition systems. The processor automatically captures images via the 360-degree camera, processes these images to extract participant identities, and performs actions based on this automatic identification, thereby improving accuracy while managing complexity through automation.
Solution Approach 2:
The system introduces an intermediary image processing component that acts as a mediator between the 360-degree camera and the participant identification system. This intermediary automatically processes captured images, extracts participant identities, and provides this information to the system for action execution, thereby improving identification accuracy while isolating the complexity within a dedicated processing module.
3Speed
If biometric techniques and wireless signal analysis are used for participant identification, then identification speed improves, but resource consumption increases
Solution Approach 1:
The system applies partial action by using biometric techniques and wireless signal analysis selectively and only when needed for participant identification, rather than continuously. The processor activates these resource-intensive methods only during identification events, thereby achieving fast identification speed while minimizing overall resource consumption by avoiding unnecessary continuous operation of these features.
Data Source
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AI summary
Techniques are described herein that are capable of performing action(s) based on automatic participant identification. For example, participants of a meeting may be automatically identified independently from an invitee list for the meeting. In another example, participants of the meeting may be automatically identified even if such participants are not indicated by the invitee list. An action is performed with regard to the participants of the meeting based at least in part on the participants being automatically identified.