Image Tracking with Position-Adaptive Feature Mixing in Fisheye Views
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Solution Overview
Problem
The feature quantity of a target object captured with a fisheye camera varies depending on its relative position to the camera, affecting tracking precision.
Innovation Solution
An image processing apparatus that tracks a target using a combination of color and shape features, adjusting the mixing ratio based on the target's position within the imaging range to improve tracking accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single feature tracker is used to track the target, then the device complexity is low, but the tracking precision deteriorates due to feature variation in fisheye images
Solution Approach 1:
The tracking system is segmented into multiple feature trackers, each specialized for different types of features (color, shape, texture). This segmentation allows each tracker to focus on specific feature types that are more stable under certain conditions, thereby improving overall tracking precision while managing complexity through functional division
Solution Approach 2:
Multiple feature trackers are merged into a unified tracking framework where their outputs are integrated. The segmentation results from different feature trackers are combined to produce a final tracking decision, leveraging the complementary strengths of each feature type to achieve robust tracking across varying fisheye image conditions
2Measurement precision
If multiple feature trackers are used to improve tracking precision, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
Different feature trackers are assigned to track different aspects of the target based on local image characteristics. For example, color features may be prioritized in certain regions while shape features are used in others, allowing each tracker to operate optimally in its designated domain and improving precision without requiring all trackers to process all data
Solution Approach 2:
An intermediary module is introduced to manage the outputs from multiple feature trackers. This mediator integrates the segmentation results, resolves conflicts between different trackers, and produces a unified tracking decision, thereby managing the complexity introduced by multiple trackers while maintaining high precision
3Reliability
If feature tracking is performed without position-based adjustment, then the ease of operation is high, but the reliability deteriorates due to unstable feature detection in different imaging ranges
Solution Approach 1:
The feature selection and weighting in the tracking system are made dynamic based on the target's position in the imaging range. As the target moves across different regions of the fisheye image, the system dynamically adjusts which features are prioritized and how they are weighted, ensuring reliable tracking adaptability without requiring manual reconfiguration
Solution Approach 2:
The system automatically changes tracking parameters such as feature weights, tracker activation, and detection thresholds based on the target's position and imaging conditions. This parameter adaptation ensures optimal tracking reliability across different imaging ranges while maintaining ease of operation through automated adjustment rather than manual intervention
Data Source
AI summary
An image processing apparatus includes a tracking target setter that sets a tracking target in a first frame of a video, a first feature tracker that tracks the tracking target in a second frame based on a first feature of the tracking target set in the first frame, a second feature tracker that tracks the tracking target in the second frame based on a second feature of the tracking target set in the first frame, a tracking manager that mixes a tracking result obtained by the first feature tracker with a tracking result obtained by the second feature tracker at a predetermined mixing ratio, and an output unit that outputs a detection position of the tracking target in the second frame based on a mixing result obtained by the tracking manager.