HDR Camera Relative Motion Detection via Segmented Characteristics Curve
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Solution Overview
Problem
Existing image recording systems in vehicles require multiple images to determine relative motion, which is time-consuming and less accurate due to motion blur, especially in varying illumination conditions.
Innovation Solution
A method utilizing an HDR camera with a characteristics curve having break points, allowing relative motion estimation from a single image by measuring distances between reset points and calculating velocity based on pixel brightness transitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images are used to determine relative motion, then measurement accuracy is improved, but detection time increases and productivity decreases
Solution Approach 1:
The characteristics curve is segmented into multiple linear segments with different slopes, where each segment corresponds to a specific brightness range. By detecting which segment an object falls into and measuring its position within that segment, the system can determine relative motion from a single image frame, eliminating the need for multiple frames while maintaining accuracy.
Solution Approach 2:
The patent changes the parameter of the characteristics curve by introducing break points that create segments with different slopes. This allows the system to encode both brightness information and motion information in a single image, enabling accurate relative motion detection without requiring multiple images or temporal sequences.
2Device complexity
If conventional image sensors with fixed characteristics curves are used, then device complexity is reduced, but adaptability to varying illumination conditions deteriorates
Solution Approach 1:
The characteristics curve is made dynamic by allowing different linear segments to be activated based on the object's brightness level. The break points in the characteristics curve enable the sensor to automatically adapt to varying illumination conditions without requiring complex real-time adjustment mechanisms, achieving adaptability while maintaining relatively simple device architecture.
3Loss of time
If motion blur methods are used for velocity measurement, then detection time is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent replaces the mechanical/optical motion blur method with an electronic/image-processing-based method. Instead of relying on physical blur effects during exposure, the system uses the segmented characteristics curve to encode motion information in the brightness transitions between segments, achieving accurate velocity measurement without motion blur while maintaining fast detection time.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables faster and more accurate detection of relative motion, including velocity and direction, even in challenging illumination conditions, facilitating timely risk assessment and mitigation of collision risks.
Implementation Method 1
an image sensor and one optical system associated with this image sensor, which maps a recorded field of the vehicle's surroundings onto the image sensor
Data Source
AI summary
In a method for detecting a motion of an object with the aid of an image recording system (e.g., HDR camera) which includes an image sensor, a first reset and a second reset are performed at a time interval during the exposure of the image sensor, an extent of a region of constant brightness is measured from the image of an object, and the motion (direction, velocity, and optionally acceleration) of the object is ascertained from the relationship between the measured extent and the time interval between the first and second resets. This motion determination is achieved with the aid of a single image.