ADAS Camera Pose Recognition for Accurate Object Distance
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Solution Overview
Problem
Advanced driver assistance systems (ADAS) face challenges in accurately recognizing the pose of cameras mounted on vehicles due to changes in vehicle pose caused by topography and external forces, leading to errors in distance measurement to objects.
Innovation Solution
The system uses optical flow and vanishing points from images to recognize the camera pose, corrects distance errors, and generates a top view by weighting relative pose data and trajectory data based on Gaussian fitting coefficients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vehicle pose estimation using VDC is performed to compensate for distance error, then distance measurement accuracy is improved, but error accumulation occurs due to chronological estimation of pose changes
Solution Approach 1:
The patent replaces the mechanical/chronological pose estimation method (VDC) with an optical-based approach using vanishing points and optical flow from camera images. This substitution eliminates the accumulation of errors over time by directly calculating pose from visual features rather than integrating sequential pose changes.
Solution Approach 2:
The patent introduces vanishing points and optical flow as intermediary elements to bridge the gap between image data and pose estimation. These intermediaries provide a direct geometric relationship between the camera and the scene, enabling accurate pose calculation without chronological integration.
2Measurement precision
If camera pose recognition is performed to correct distance errors, then distance measurement accuracy is improved, but system complexity increases due to additional processing requirements
Solution Approach 1:
The system uses the camera's own images to determine its pose without requiring external sensors or complex calibration equipment. By extracting vanishing points and optical flow from the images themselves, the system performs self-calibration and pose estimation, reducing overall system complexity.
Solution Approach 2:
The patent introduces vanishing points and optical flow as intermediary elements to bridge the gap between image data and pose estimation. These intermediaries provide a direct geometric relationship between the camera and the scene, enabling accurate pose calculation without chronological integration.
Data Source
AI summary
An advanced driver assistance system (ADAS) includes a communicator configured to communicate with a camera; and a processor configured to: receive a first image and a second image obtained by the camera, obtain a plurality of first feature points based on the received first image, obtain a plurality of second feature points based on the received second image, obtain a plurality of first and second feature points matching each other among the plurality of first feature points and the plurality of second feature points, obtain an optical flow and a vanishing point based on the plurality of first and second feature points matching each other, recognize a pose of the camera based on the optical flow and the vanishing point, and correct a distance to an object in the second image based on the recognized pose of the camera.