Teleoperation Image Compression Using ROI-Based Quality Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The challenge in remote vehicle operation is to transmit high-quality, real-time image data with low latency over limited bandwidth wireless networks without compromising image resolution, as over-compression can result in loss of important details.
Innovation Solution
The method involves selectively compressing image data by identifying regions of interest based on the remote operator's direction or focus, using sensors and image processing logic to generate and compress visual representations, with regions of interest compressed to a lesser extent than others, ensuring higher quality and reducing data transmission while maintaining critical details.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If image data is compressed to reduce data transmission, then bandwidth usage is optimized, but image resolution and quality deteriorate
Solution Approach 1:
The patent divides the image into multiple regions of interest (ROIs) and non-ROI areas, applying different compression strategies to each segment. ROI areas maintain higher resolution while non-ROI areas use aggressive compression, resolving the contradiction between overall data reduction and local quality preservation.
Solution Approach 2:
Different compression quality levels are applied to different spatial regions of the image based on their importance. Critical regions (ROIs) receive minimal compression to preserve detail, while less important regions undergo heavy compression, optimizing the trade-off between total data volume and essential image quality.
2Manufacturing precision
If image quality is maintained at high resolution, then remote operator can see critical details, but data transmission bandwidth increases
Solution Approach 1:
The image is segmented into ROI and non-ROI regions, allowing selective transmission of high-quality data only where necessary. This segmentation enables the system to maintain critical image quality while dramatically reducing overall bandwidth consumption through aggressive compression of non-critical areas.
Solution Approach 2:
The compression parameter (quality level) is dynamically changed based on spatial location within the image. ROI areas use low compression ratios to preserve quality, while non-ROI areas use high compression ratios to reduce bandwidth, optimizing the quality-bandwidth trade-off through parameter variation.
3Loss of time
If compression is applied to reduce latency, then real-time transmission is achieved, but important details are lost
Solution Approach 1:
By segmenting the image into ROI and non-ROI areas, the patent ensures that detail information is preserved in critical regions while allowing compression in non-critical regions. This segmentation enables real-time transmission with minimal latency while preventing loss of important details in ROI areas.
Solution Approach 2:
The system uses feedback from the remote operator's gaze direction and attention focus to dynamically identify ROIs, ensuring that the most relevant details are always preserved in high quality. This feedback mechanism adapts the compression strategy in real-time to maintain critical information while reducing overall data transmission.
Data Source
AI summary
Techniques are described for compressing image data for transmission to a computer system of a remote operator controlling a vehicle. A visual representation of a surrounding environment is generated from one or more images captured at the vehicle. One or more regions of interest in the visual representation are identified based at least on information received from the computer system of the remote operator, the information indicating a direction or area of focus of the remote operator. Regions of interest can be compressed to a lesser extent than regions located outside the regions of interest. The compressed visual representation is transmitted to the computer system for decompression and, ultimately, display on one or more display devices viewed by the remote operator.