Target Region Prediction for Bandwidth-Limited Image Processing
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Solution Overview
Problem
Existing image processing systems fail to accurately predict the movement of targets, leading to deviations in the regions subjected to image processing, which can degrade recognition accuracy when bandwidth is limited.
Innovation Solution
An information processing device and system that predicts target movement by analyzing consecutive image frames using a Kalman filter, determining an image-processing region by adding a margin based on the overlapping portion between detected and predicted target regions, and prioritizing high-quality image processing for critical areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image processing is performed on a target region with a fixed margin at time t, then the processing region is well-defined at that moment, but the region deviates from the actual target at time t+1 when the target is moving
Solution Approach 1:
The system performs preliminary prediction of the target's future position using a Kalman filter before executing image processing. By predicting the target region in advance (at time t) based on historical movement data, the system ensures that the image processing region accurately covers the target even when it moves during transmission or processing delays
Solution Approach 2:
The system uses feedback from detected target positions across multiple time frames to continuously update and refine position predictions. The Kalman filter incorporates actual target detection results from previous frames to correct prediction errors and improve accuracy for the current frame's image processing region determination
2Reliability
If the margin width is increased to ensure target visibility, then the target remains visible even with position deviations, but the image processing region becomes larger than necessary
Solution Approach 1:
Instead of using a fixed margin width, the system dynamically adjusts the margin based on the predicted target position and the calculated overlapping region. The margin is optimized to be just large enough to cover the predicted target area, adapting to the target's movement characteristics and reducing unnecessary processing regions
Solution Approach 2:
The system changes the margin parameter dynamically based on prediction accuracy and target movement patterns. By adjusting the margin width according to the specific situation (using overlapping region calculations), the system maintains target visibility while minimizing the image processing region area
3Ease of manufacture
If image processing is performed on all regions with uniform quality, then processing is simple, but bandwidth is wasted on non-critical areas
Solution Approach 1:
The system applies different image processing qualities to different regions based on their importance. The determined target region receives high-quality processing with finer quantization, while other regions use lower-quality processing with coarser quantization, optimizing bandwidth usage while maintaining recognition accuracy for critical areas
Solution Approach 2:
The image is segmented into different processing zones: the determined target region (requiring high quality) and other regions (acceptable for lower quality). This segmentation allows the system to apply appropriate processing strategies to each region, simplifying the overall processing while conserving bandwidth
Data Source
AI summary
A region prediction unit predicts the target region in the second image frame based on the target region detected in a first image frame and a time interval between the first and second image frames. The region prediction unit predicts the target region in the third image frame based on the target region detected in the second image frame and a time interval between the second and third image frames. A region determination unit determines, as an image-processing region, a region obtained by adding a margin to the target prediction region in the third image frame in accordance with an overlapping portion between the detected target region in the second image frame and the prediction region in the second image frame.