Dynamic Frame Count Adjustment for In-Vehicle Object Recognition
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Solution Overview
Problem
Existing image processing systems for in-vehicle cameras face challenges in accurately recognizing objects, particularly when the vehicle's conditions or the object's movement speed affect the recognition process, leading to potential delays in collision avoidance systems.
Innovation Solution
An image processing apparatus that includes an image acquisition unit, an object candidate recognition unit, an object determination unit, a parameter X acquisition unit, and an N setting unit, which adjusts the number of consecutive frames (N) required for object recognition based on parameters like moving speed, distance, and vehicle conditions to enhance recognition accuracy and responsiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the same object is required to be recognized in a fixed number of consecutive frames (fixed N), then recognition accuracy is improved, but responsiveness to rapidly moving objects deteriorates
Solution Approach 1:
The patent applies dynamics by making the threshold N variable rather than fixed. The N setting unit dynamically adjusts the number of consecutive frames required for object recognition based on the apparent moving speed of the object. When an object is detected to be moving rapidly, N is reduced to enable faster recognition and response. When objects are stationary or moving slowly, N is increased to maintain high recognition accuracy. This dynamic adjustment resolves the contradiction between accuracy and responsiveness.
Solution Approach 2:
The patent changes the parameter N (number of consecutive frames required) based on the apparent moving speed parameter. The parameter X acquisition unit obtains information about apparent moving speed, and the N setting unit uses this to adjust N accordingly. This parameter change strategy allows the system to adapt the recognition threshold to match the motion characteristics of detected objects, improving both accuracy for stationary objects and responsiveness for moving objects.
2Device complexity
If a fixed threshold N is used for all objects, then system complexity is reduced, but adaptability to different moving speeds deteriorates
Solution Approach 1:
The system introduces dynamic adaptability by making N variable based on apparent moving speed. The N setting unit automatically adjusts N according to the motion characteristics of each detected object, enabling the system to adapt to different scenarios without manual intervention. This maintains low operational complexity while achieving high adaptability.
Solution Approach 2:
The system performs self-adjustment by automatically setting appropriate N values based on the apparent moving speed of detected objects. The parameter X acquisition unit and N setting unit work together to autonomously determine the optimal recognition threshold for each situation, eliminating the need for external configuration or manual tuning and thereby maintaining system simplicity while achieving adaptability.
Data Source
AI summary
An image processing apparatus includes an image acquisition unit that uses a camera installed in an own vehicle to acquire images of an environment outside the own vehicle at predetermined intervals, an object candidate recognition unit that recognizes an object candidate in the image, an object determination unit that determines that the object candidate is an object on condition that the same object candidate is recognized in N consecutive frame images (N is a natural number), a parameter X acquisition unit that acquires a parameter X correlated with an apparent moving speed of a stationary object in the images, and an N setting unit that sets N smaller as the moving speed correlated with a value of the parameter X increases.