Stereo Camera Redundant Object Detection
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Solution Overview
Problem
Current driver assistance systems rely on multiple sensors for redundant object detection, which complicates installation and cabling, and provides less accurate object localization and error protection compared to using a single stereo camera for redundant object detection.
Innovation Solution
Implementing a stereo camera with two image sensors and dual processing paths, where the first path detects objects through stereo image evaluation and the second path classifies these objects using image data from at least one sensor, providing redundant object detection and accurate pixel-accurate localization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple sensors (radar and camera) are used for redundant object detection, then detection reliability is improved, but device complexity and installation difficulty increase
Solution Approach 1:
The patent combines two separate sensors (radar and camera) into a single integrated sensor unit that performs both functions. The sensor module includes a radar sensor and a camera sensor integrated within the same housing, sharing common structural elements and mounting mechanisms. This merging reduces the number of separate components to be installed and connected, thereby reducing device complexity while maintaining the redundancy benefits of using both sensor types for object detection
Solution Approach 2:
The integrated sensor module is designed to perform multiple functions simultaneously - both radar-based object detection and camera-based object detection and classification. The single sensor unit serves as both a radar sensor and a camera sensor, eliminating the need for separate dedicated sensors for each function. This multi-functionality approach reduces installation complexity while maintaining detection reliability through redundant detection paths
2Reliability
If multiple sensors are used for redundant object detection, then error protection is improved, but installation and cabling becomes more complex
Solution Approach 1:
The patent merges multiple sensors into a single integrated module with shared mounting structure, housing, and connection interfaces. The sensor module includes integrated electronics that process signals from both radar and camera sensors through common processing circuits. This consolidation reduces the number of separate mounting operations, cable connections, and alignment procedures required during installation, making the system easier to install while maintaining error protection through redundant detection
3Measurement precision
If a stereo camera with dual processing paths is used, then object classification accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent segments the object detection and classification process into two distinct processing paths: a first processing path that detects objects using stereo image evaluation, and a second processing path that classifies the detected objects using image data from at least one of the two image sensors. This segmentation allows each path to be optimized for its specific function, with the first path focusing on accurate object localization and the second path focusing on object classification, thereby improving overall accuracy while managing processing complexity through functional decomposition
Solution Approach 2:
The patent introduces an intermediary object list that stores detected objects from the first processing path before they are passed to the second processing path for classification. This intermediary structure allows the two processing paths to operate semi-independently, with the object list serving as a buffer that decouples the timing and processing requirements of detection and classification. This mediator approach manages processing complexity by allowing parallel or sequential execution of the two paths without requiring tight synchronization
Data Source
AI summary
A device for redundant object detection includes a stereo camera having two image sensors, a first processor for detecting objects by stereo image evaluation of image data from the two image sensors, and a second processor for classifying the detected objects by evaluation of image data from at least one of the two image sensors. A method and a program for such object detection and classification are also provided.