Visual Target Tracking Using Frame-to-Frame Spatial Adjustment
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Solution Overview
Problem
Existing visual tracking methods for moving targets are inadequate when the aerial vehicle or camera is at different spatial dispositions relative to the target, such as varying heights, distances, or orientations, as they fail to accurately account for these changes, leading to reduced tracking precision and the need for manual intervention.
Innovation Solution
A method and apparatus that determine changes in features between image frames captured at different times to adjust the movement of a movable object, such as an unmanned aerial vehicle (UAV), to maintain tracking of a target object, even when the object and imaging device are at different spatial dispositions, using processors to analyze images and control the UAV's movement based on changes in the target's size and position within the frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing visual tracking methods are used, then the system can track a target object, but the tracking precision deteriorates when the aerial vehicle or camera is at different spatial dispositions relative to the target
Solution Approach 1:
The patent transforms 2D image coordinates into 3D spatial coordinates by introducing depth information and spatial transformation parameters. This allows the system to account for varying heights, distances, and orientations between the aerial vehicle and target, maintaining tracking precision across different spatial dispositions without requiring manual intervention for each configuration change.
2Measurement precision
If manual control is used to maintain tracking accuracy, then the tracking precision can be maintained, but the ease of operation deteriorates due to the need for continuous manual intervention
Solution Approach 1:
The system performs autonomous spatial transformation and target tracking without requiring manual control inputs. The processor automatically transforms image coordinates to spatial coordinates, calculates the target's position and movement, and adjusts tracking parameters independently, eliminating the need for continuous manual intervention while maintaining high tracking accuracy.
Solution Approach 2:
The system uses feedback from consecutive image frames to continuously update the target's spatial position and movement trajectory. By comparing the transformed coordinates across multiple frames, the system automatically adjusts tracking parameters to maintain accuracy, replacing manual control with an automated feedback-driven tracking mechanism.
3Adaptability or versatility
If the system accounts for spatial dispositions, then the adaptability improves, but the device complexity increases due to additional processing requirements
Solution Approach 1:
The patent divides the complex spatial transformation process into distinct computational stages: (1) detecting target coordinates in image frames, (2) transforming 2D image coordinates to 3D spatial coordinates using depth and orientation parameters, (3) calculating spatial displacement between frames, and (4) updating tracking parameters. This segmentation of the processing pipeline manages complexity by organizing operations into modular, sequential steps that can be independently optimized.
Data Source
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AI summary
A method for controlling a movable object to track a target object may be provided. The method may comprise: determining a change in one or more features between a first image frame and a second image frame, wherein the one or more features are associated with the target object, and wherein the first image frame and the second image frame are captured at different points in time; and adjusting a movement of the movable object based on the change in the one or more features between the first image frame and the second image frame.