Image Framing Layout for Automatic Out-of-Frame Subject Tracking
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Solution Overview
Problem
Existing image processing systems struggle to efficiently track subjects that move out of the visible frame during dynamic image capture, requiring manual user intervention to reposition the device for continued tracking.
Innovation Solution
An image processing device sets a smaller central output target region within the frame image and monitors potential subject movement outside this region using out-of-frame monitor regions, automatically adjusting the output target region to recenter the subject within the visible frame.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the output target region is set to cover the entire frame image region, then complete subject visibility is maintained, but data processing load increases and frame capture efficiency decreases
Solution Approach 1:
The frame image region is divided into multiple regions: a central output target region for primary subject capture and high-quality processing, and peripheral out-of-frame monitor regions for subject detection and tracking. This segmentation allows the system to process only the central region at high quality while using peripheral regions for efficiency, resolving the contradiction between complete visibility and processing efficiency.
2Device complexity
If manual user intervention is required to reposition the device for continued tracking, then processing load is reduced, but ease of operation deteriorates
Solution Approach 1:
The system automatically detects subjects in out-of-frame monitor regions and adjusts the output target region positioning without requiring manual user intervention. The processing unit autonomously determines when subjects appear in peripheral regions and repositions the central output target region to maintain subject visibility, eliminating the need for manual device repositioning while maintaining reasonable processing loads.
3Productivity
If the output target region is reduced to a smaller central area, then data processing load and bandwidth requirements decrease, but the area for detecting out-of-frame subjects must be carefully managed
Solution Approach 1:
The system extends detection capability beyond the central output target region by utilizing out-of-frame monitor regions in the peripheral areas. This dimensional extension allows the system to detect subjects that have moved outside the primary capture area, maintaining efficient processing of the central region while expanding the effective detection scope through strategically positioned peripheral monitor regions.
Data Source
AI summary
An image processing device including a processing unit, in whichin a position in a central part of a frame image region related to a plurality of frame images, an output target region smaller than the frame image region is set as a range for which image data is output, andan out-of-frame monitor region to be a target for detecting a subject is set in a position deviated in a predetermined direction from the central part, in a part of the frame image region outside the output target region.