Eye Gazing Video System with Dynamic Field of View
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Solution Overview
Problem
Current video communication systems are not adequately optimized for residential environments, lacking flexibility in managing privacy and contextual information, and are not well-suited for dynamic situations, which affects the user experience and privacy concerns.
Innovation Solution
A video communication system that includes an image display device, image capture devices, an audio system, a computer with a contextual interface and image processor, and a communication controller, which uses scene analysis algorithms to adapt image capture and processing for eye contact and manage privacy settings, allowing users to control image capture and transmission in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed field of view camera is used, then the system is simple and cost-effective, but it cannot adapt to dynamic residential environments and loses contextual information
Solution Approach 1:
The patent implements dynamic field of view adjustment through multiple cameras with different focal lengths and adjustable optical zoom. The system transitions from a static single-viewpoint camera to a dynamic multi-viewpoint system that can adapt its capture scope in real-time based on scene analysis, enabling it to handle both close-up and wide-context scenarios in residential environments.
Solution Approach 2:
The system divides the imaging function into multiple independent camera modules, each with specific field of view characteristics. By segmenting the capture function across multiple devices with different capabilities, the system achieves versatility in handling various scene types while maintaining manageable complexity through modular architecture.
2Loss of information
If multiple cameras with different fields of view are used, then contextual information is captured, but the system complexity increases
Solution Approach 1:
The system employs scene analysis algorithms that continuously process camera feeds to identify objects, their spatial relationships, and contextual significance. This feedback loop enables the system to automatically select appropriate cameras and adjust field of view based on real-time scene understanding, preventing contextual information loss while managing complexity through intelligent automation.
Solution Approach 2:
Multiple cameras are designed with multi-functionality, where each camera can serve different purposes (close-up capture, wide-context capture, eye-contact capture) depending on the scene requirements. This universal design allows a single camera system to handle diverse residential scenarios without requiring separate specialized systems for each function.
3Ease of operation
If automatic camera control is implemented, then ease of use is improved, but user control over privacy settings is reduced
Solution Approach 1:
The system implements self-service through automatic scene analysis and camera selection, where the system independently determines which camera to activate and what field of view to use based on detected objects and user actions. This automation improves ease of use while maintaining privacy control through transparent indicators and user-activatable overrides.
Solution Approach 2:
The system performs preliminary scene analysis and camera selection before capturing images or video, automatically determining the appropriate capture parameters based on pre-detected objects and contextual information. This preliminary action streamlines the user experience while preserving privacy control through advance notification and user-activatable settings.
4Manufacturing precision
If eye contact image capture is prioritized, then communication quality is enhanced, but the field of view is restricted
Solution Approach 1:
The system segments the field of view into multiple overlapping zones covered by different cameras with different focal lengths. By dividing the capture area into segments, the system can selectively activate cameras optimized for specific tasks (eye contact vs. wide context) without being forced to choose one exclusively, thus maintaining both precision and field of view flexibility.
Solution Approach 2:
The system adds a temporal dimension to the field of view selection, where different cameras and field of view settings can be activated at different times based on the scene requirements. This temporal multiplexing allows the system to provide eye-contact precision when needed while maintaining wide field of view coverage when context is important, without compromising either capability.
Data Source
AI summary
Video communication systems and methods for communicating between an individual in a local environment, and a remote viewer in a remote environment are provided. The system has an image display device; at least one image capture device which acquires video images for fields of view of a local environment, and any individuals therein; an audio system having an audio emission device and an audio capture device; a computer, which includes a contextual interface having a gaze adapting process, and image processor; and a communication controller which transmits and receives video images of the local environment and the remote environment, and data regarding video scene characteristics thereof across a network between the local environment and the remote environment; wherein the gaze adapting process identifies video scene characteristics of the local environment indicative of eye gaze image capture and altering the video images when the characteristics are indicative.