Target Tracking via Camera Projection and SLAM Recovery
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Solution Overview
Problem
Current target tracking methods in video processing face challenges with fast camera movement and poor robustness, leading to inaccurate recognition and tracking of video content.
Innovation Solution
A target tracking method that acquires a target video frame, determines position information of a target area, and if failed, uses camera projection and simultaneous localization and mapping algorithms to re-determine the position, ensuring tracking recovery even during fast camera movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If edge features are used for target tracking in video frames, then the tracking process is simple, but the tracking fails when camera moves fast and robustness is poor
Solution Approach 1:
The patent segments the tracking process into multiple stages: initial target detection, track establishment, and track maintenance. By dividing the complex tracking task into manageable segments with different strategies for detection and maintenance phases, the system achieves both simplicity and robustness.
Solution Approach 2:
The patent performs preliminary target detection and establishes tracking tracks in advance before actual tracking begins. This preliminary action ensures that when camera movement occurs, the tracking system already has established tracks to maintain, preventing tracking failure during fast camera movement.
2Ease of manufacture
If traditional target tracking methods are used, then the implementation is straightforward, but accuracy is low and requirements for video content recognition and tracking are not met
Solution Approach 1:
The patent implements feedback mechanisms where detection results from previous frames inform tracking in current frames, and tracking status feeds back to adjust detection strategies. This continuous feedback loop improves tracking accuracy while maintaining implementation feasibility through standardized feedback processing steps.
Solution Approach 2:
The patent dynamically adjusts tracking parameters such as search window size, detection thresholds, and matching criteria based on track confidence levels and camera movement detection. These parameter changes enable the system to adapt to different scenarios, improving accuracy without requiring completely different implementation approaches.
3Speed
If camera moves fast, then video capture coverage is improved, but target detection fails and tracking robustness deteriorates
Solution Approach 1:
The patent prepares cushioning measures in advance by establishing multiple candidate tracks and pre-computing search regions based on predicted target motion. When fast camera movement occurs, these pre-prepared tracks and search regions prevent detection failure, cushioning against the adverse effects of rapid camera motion.
Solution Approach 2:
The patent makes the tracking system dynamic by adapting search strategies, window sizes, and detection parameters in real-time based on detected camera movement magnitude and direction. This dynamic adjustment allows the system to maintain detection reliability even when camera moves fast, transforming a static vulnerable system into a resilient adaptive one.
Data Source
AI summary
The present disclosure relates to a target tracking method and apparatus, a device, and a medium. The method includes: acquiring a target video frame; determining, based on the target video frame, position information of a target area in the target video frame; in a case that a determination of the position information of the target area in the target video frame is failed, determining target photographing position information, and determining again, according to the target photographing position information and a camera projection algorithm, the position information of the target area in the target video frame.