Vehicle Object Detection Using Dual Camera Displacement Analysis
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Solution Overview
Problem
Conventional object detection systems for vehicles face challenges in accurately determining the position and shape of objects using single sensors, such as radar sensors recognizing position information but not shape, and cameras recognizing shape but struggling with position information, necessitating the use of multiple sensors for comprehensive detection.
Innovation Solution
An object detection apparatus and method utilizing two camera systems, including a first camera unit capturing images around the vehicle and a second camera unit capturing images ahead, with a control unit determining displacement and pixel displacement of feature points to calculate distance information and generate bounding boxes, potentially aided by a lamp module for illumination and feature point generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single camera is used for object detection, then the system complexity is reduced, but the ability to accurately determine both position and shape information deteriorates
Solution Approach 1:
The patent combines two different camera systems (first camera unit with wide FOV and second camera unit with telephoto lens) into a unified object detection system. The control unit integrates images from both cameras to simultaneously obtain accurate position information from the wide-FOV camera and detailed shape information from the telephoto camera, resolving the contradiction between system simplicity and detection accuracy.
Solution Approach 2:
The patent makes the camera system multi-functional by using two cameras with different characteristics. The first camera unit provides wide-area coverage for position detection, while the second camera unit provides magnified views for shape recognition. This multi-functionality allows a single detection system to perform both position and shape analysis effectively.
2Measurement precision
If radar sensors are used for object detection, then position information is easily obtained, but shape recognition capability deteriorates
Solution Approach 1:
The patent merges the advantages of radar-like position detection (achieved through the first camera unit with wide FOV) with camera-based shape recognition (achieved through the second camera unit with telephoto lens). The control unit processes images from both cameras to extract both position and shape information, eliminating the need to choose between radar and camera systems.
3Shape
If cameras are used for object detection, then shape information is easily obtained, but position information accuracy deteriorates
Solution Approach 1:
The patent combines the shape recognition capability of cameras with the position detection capability of wide-FOV cameras. The first camera unit captures wide-area images for accurate position determination, while the second camera unit captures magnified images for detailed shape analysis. The control unit integrates both types of information to achieve comprehensive object detection.
4Measurement precision
If multiple sensors are used for comprehensive object detection, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The patent uses two camera units that serve multiple functions within the same detection system. Rather than combining fundamentally different sensor types (radar, lidar, camera), the system uses two cameras with different focal characteristics, both of which capture optical images. This approach achieves comprehensive detection accuracy while maintaining relatively simple system architecture and image processing requirements.
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 accurate detection of distance and bounding boxes of objects without relying on radar or lidar sensors, improving recognition performance in severe environments like low illuminance and backlight conditions, and enhancing image quality through light emission and image coupling.
Implementation Method 1
a lamp module configured to illuminate the common area
Implementation Method 2
The first camera unit includes one or more cameras, and is configured to capture an image around a vehicle. The second camera unit includes one or more cameras, and is configured to capture an image of an area ahead of the vehicle.
Data Source
AI summary
An object detection apparatus includes a first camera unit, a second camera unit, and a control unit. The first camera unit includes one or more cameras, and is configured to capture an image around a vehicle. The second camera unit includes one or more cameras, and is configured to capture an image of an area ahead of the vehicle. The control unit is configured to: determine a displacement of a feature point positioned in a common area from the image acquired via the first camera unit; determine a pixel displacement of the feature point in the image acquired via the second camera unit; and determine distance information to an object recognized in the image captured via the second camera unit based on the displacement of the feature point and the pixel displacement of the feature point.