Gesture Recognition for Videoconference Feedback Control
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Solution Overview
Problem
Existing videoconference technologies limit participants' ability to provide meaningful feedback, as they are often restricted from transmitting audio and have smaller interface portions, making it difficult for non-primary speakers to contribute during a session.
Innovation Solution
Implementing gesture recognition and speech-to-text processing to identify requests for feedback within content streams, allowing participants to provide feedback through gestures like thumbs up or down, which can initiate actions such as selecting a new primary presenter or presenting content items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If participants are restricted from transmitting audio and have smaller interface portions, then the primary speaker's presentation quality is improved, but the ability of non-primary speakers to provide feedback deteriorates
Solution Approach 1:
The patent introduces gesture recognition as an intermediary mechanism that enables non-primary speakers to provide feedback without transmitting audio. The system detects gestures (such as hand movements) from video feeds and translates them into feedback signals, allowing participants to contribute meaningfully while maintaining the audio restrictions that protect primary speaker quality.
Solution Approach 2:
The patent replaces the traditional audio-based feedback mechanism with a visual gesture-based system. Instead of using sound waves (acoustic energy) for feedback, the system uses visual detection of physical gestures and processes them through computer vision algorithms to generate feedback, substituting a mechanical/visual system for an acoustic one.
2Adaptability or versatility
If multiple participants are enabled to provide feedback, then collaboration quality is improved, but system complexity increases
Solution Approach 1:
The patent makes the gesture recognition system serve multiple functions: it can detect various types of gestures (hand raises, thumbs up/down, pointing), identify different emotional states, and trigger multiple types of feedback actions. This universal gesture interface replaces multiple separate feedback mechanisms (audio, chat, voting tools), reducing overall system complexity while improving collaboration quality.
Solution Approach 2:
The system automatically processes gestures detected from video feeds without requiring manual intervention. The gesture recognition and feedback generation occur autonomously through automated image processing and pattern recognition, eliminating the need for complex manual feedback management interfaces.
Data Source
AI summary
Systems and methods are disclosed for gesture-initiated actions in videoconferences. In one implementation, a processing device receives content streams during a communication session, identifies a request for feedback within one of the content streams, based on an identification of the request for feedback, processes the content streams to identify one or more gestures within at least one of the content streams, and based on a determination that a first gesture of the one or more gestures is relatively more prevalent across the content streams than one or more other gestures, initiates an action with respect to the communication session.