Gaze Controlled Bit Rate for Video Monitoring
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Solution Overview
Problem
Monitoring systems with multiple cameras face high network bandwidth consumption and resource utilization due to continuous video streaming, as operators can only focus on a portion of the display at a time, leading to inefficiencies in resource allocation.
Innovation Solution
Implementing an eye tracking sensor to identify the operator's gaze area and generate a gradient for bit rate reduction outside the gaze area, adjusting bit rates, sampling rates, and compression parameters to conserve network resources and reduce processor load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video streams from multiple cameras are transmitted at high bit rates to maintain quality, then image quality is improved, but network bandwidth consumption increases
Solution Approach 1:
The patent applies local quality by transmitting video data at different bit rates for different regions of the video stream. Specifically, the video stream is divided into a gaze area (where the operator is looking) and non-gaze areas, with higher bit rates allocated to the gaze area to maintain image quality, and lower bit rates allocated to non-gaze areas to reduce network bandwidth consumption.
Solution Approach 2:
The patent implements dynamic bit rate adjustment by continuously tracking the operator's gaze position and adapting the video transmission parameters in real-time. The system dynamically identifies the gaze area using eye tracking technology and adjusts the bit rate distribution accordingly, allowing the quality of transmission to change based on the operator's current focus rather than maintaining a static high bit rate for the entire stream.
2Measurement precision
If video streams are transmitted at high bit rates to maintain quality, then image quality is improved, but processor load and memory usage increase
Solution Approach 1:
The system reduces processor load and memory usage by applying different processing intensities to different regions of the video stream. High-quality processing (decoding, rendering) is applied only to the gaze area, while non-gaze areas receive reduced processing, thereby lowering the overall computational burden on processors and memory resources while maintaining acceptable image quality in the relevant region.
Solution Approach 2:
The system dynamically adjusts processing resources based on the operator's gaze position. By continuously tracking where the operator is looking and adapting the processing intensity in real-time, the system ensures that computational power and memory are concentrated on the most relevant portions of the video stream, avoiding the waste of processing resources on areas that the operator is not currently observing.
3Measurement precision
If uniform bit rate is applied across the entire video stream, then image quality is maintained consistently, but network resources are wasted in areas not being observed
Solution Approach 1:
The patent implements local quality by allocating different bit rates to different spatial regions of the video stream based on the operator's gaze position. The gaze area receives higher bit rates to maintain image quality consistency in the observed region, while non-gaze areas receive lower bit rates, thereby preventing network resource waste in unobserved regions while preserving quality where it matters most.
Solution Approach 2:
The system dynamically redistributes network resources based on real-time gaze tracking data. Instead of maintaining a static uniform bit rate, the system continuously adapts the bit rate allocation to match the operator's current focus, ensuring that network bandwidth is concentrated on the relevant portions of the video stream and reduced in irrelevant areas, thus eliminating resource waste while maintaining quality consistency in the gaze area.
Data Source
AI summary
A method may include receiving a video stream from a camera and displaying the video stream on a display. The method may further include obtaining, via an eye tracking sensor, information identifying a gaze area for a user watching the display; generating a gradient from the gaze area to edges of the display; and instructing the camera to decrease a bit rate of the video stream outside the gaze area based on the generated gradient.