Dynamic Tracking Method Switching for Power and Accuracy
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Solution Overview
Problem
Existing image processing systems for object tracking in image capturing apparatuses lack the ability to dynamically switch between different matching methods based on the image capture situation and object state, leading to suboptimal power consumption and tracking accuracy.
Innovation Solution
An image processing apparatus with a tracking unit that includes both Feature Point Matching (FPM) and Template Matching (TM) methods, allowing the system to switch between these methods based on situation information such as object type, size, movement, and autofocus mode to optimize power consumption and tracking accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If template matching method is used for object tracking, then tracking accuracy is improved, but power consumption increases
Solution Approach 1:
The system dynamically switches between template matching and feature point matching methods based on the detection result of object movement from optical flow. When movement is detected, feature point matching is used to reduce power consumption; when no movement is detected, template matching is used to maintain high tracking accuracy.
Solution Approach 2:
The system changes the matching method parameter based on the movement detection result. By using the optical flow detection result as a condition, the system selects between two different matching algorithms, optimizing the balance between accuracy and power consumption according to the current scene characteristics.
2Use of energy by moving object
If feature point matching method is used for object tracking, then power consumption is reduced, but tracking accuracy deteriorates
Solution Approach 1:
The system dynamically adjusts the matching method based on real-time movement detection. When the optical flow indicates no significant movement, the system switches to template matching to ensure high tracking accuracy, while using feature point matching only when movement is detected to conserve power.
Solution Approach 2:
The system changes the matching algorithm parameter based on the movement condition. By using conditional logic based on optical flow detection, the system selects the appropriate matching method to maintain accuracy when needed while reducing power consumption when possible.
3Measurement precision
If optical flow processing is performed, then object movement detection accuracy is improved, but processing load increases
Solution Approach 1:
The system extracts only the necessary information from optical flow processing - specifically, whether object movement is detected or not. Rather than performing full optical flow analysis, the system uses the movement detection result as a simple condition to switch between matching methods, reducing the overall processing load while maintaining effectiveness.
Data Source
AI summary
An image processing apparatus for tracking an image of a predetermined object included in an input captured image includes acquiring the captured image, executing tracking processing to identify a position of the image of the predetermined object included in the captured image, executing the tracking processing using different matching methods, acquiring situation information indicating a state of the predetermined object and/or an image capture situation of the captured image, and switching, on a basis of the situation information, to executing the tracking processing using either a first tracking unit or a second tracking unit on a basis of the captured image. The matching method used by the first tracking unit has a lower power consumption associated with executing the tracking processing than the matching method used by the second tracking unit.