Monocular Surface Orientation Detection for Lane and Vehicle Recognition
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Solution Overview
Problem
In autonomous driving and driver assist systems, incorrect determination of an object's orientation by vehicle-mounted cameras can lead to dangerous situations, such as misidentifying lane markings as vehicles or vice versa, resulting in potential collisions.
Innovation Solution
A method using a mono camera to detect and process images of a detection region before or behind a vehicle, determining the orientation of a surface by calculating a homography matrix from image coordinates, which allows for the determination of a normal vector and pitch angle, enabling reliable identification of objects like lane markings or vehicles without the need for stereoscopic images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a stereo camera system is used to determine object orientation, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces expensive stereo camera systems with a single, inexpensive mono camera. The solution uses computational methods (homography matrix calculation from sequential images) rather than expensive hardware to achieve the same measurement precision, effectively substituting a cheap single camera with multiple images for an expensive stereo camera system
Solution Approach 2:
The patent captures multiple images of the same scene from a stationary camera position before processing. By taking several photos in advance and using homography matrices to relate corresponding points across images, the system prepares the necessary data in advance to calculate surface orientation without requiring complex real-time stereo processing
2Device complexity
If a mono camera is used to determine object orientation, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent changes the approach from using spatial parameters (stereo baseline distance between cameras) to using temporal parameters (multiple images taken at different times). By capturing images sequentially and using homography matrices to relate corresponding points across time, the mono camera achieves orientation measurement capability that would normally require stereo geometry
Solution Approach 2:
The patent introduces homography matrices as an intermediary mathematical tool that bridges the gap between 2D image coordinates from a single camera and 3D orientation information. The homography matrix H relates corresponding points between images and encodes camera pose and surface orientation, acting as a mediator that enables orientation determination from monocular images
3Ease of manufacture
If sequential images are processed to determine orientation, then equipment cost is reduced, but processing time increases
Solution Approach 1:
The patent processes only the essential features from the captured images - specifically identifying corresponding points and calculating homography matrices - rather than performing exhaustive image analysis. By focusing on the minimum necessary processing (extracting key point correspondences and computing H matrices), the system achieves orientation determination with reduced processing time while maintaining accuracy
Data Source
AI summary
A method for determining the orientation of a surface of an object in a detection region before or behind a vehicle by means of a camera of the vehicle comprises the following steps: detecting a first image of the detection region by means of the camera, detecting a second image of the detection region following in time on the detecting of the first image and by means of the camera, generating of first image data corresponding to the first image and second image data corresponding to the second image, determining of eight image coordinates of four pixels each in the first image and the second image, corresponding to four points on the surface of the object, by means of the first image data and the second image data, determining of a normal vector of the surface of the object by means of the eight image coordinates, determining of the orientation of the surface of the object by means of the normal vector.