Camera-Radar Feature Fusion for Faster Vehicle Object Detection
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Solution Overview
Problem
Current radar and camera sensor systems in vehicles have limitations in object detection, with radar systems lacking resolution to identify object features and camera systems requiring additional processing for accurate classification, necessitating a method to combine their data effectively for enhanced performance in vehicle safety applications.
Innovation Solution
The method involves receiving camera and radar frames, performing feature extraction processes to generate feature maps, converting them to a common spatial domain, and concatenating or combining these maps to detect objects, utilizing an encoder-decoder network to align the data for improved object detection in spatial domains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar systems are used to detect objects, then measurement of object distance and velocity is accurate, but resolution to identify object features is insufficient
Solution Approach 1:
The patent combines radar and camera sensor data through early fusion at the feature map level. Radar feature maps containing distance and velocity information are merged with camera feature maps containing visual appearance information, creating a concatenated feature map that preserves both measurement precision and object feature identification capabilities
2Loss of information
If camera sensors are used to identify object features, then resolution to identify object features is sufficient, but additional processing is required for accurate classification
Solution Approach 1:
The patent merges camera feature maps with radar feature maps at an early stage in the processing pipeline. This early fusion approach combines visual appearance information from the camera with range and velocity information from radar, reducing the processing burden on the camera system while maintaining feature identification accuracy
Solution Approach 2:
The patent introduces an intermediary feature map concatenation step that combines radar and camera features before final object classification. This intermediary representation facilitates more efficient processing by pre-integrating complementary information from both sensors, reducing the complexity of subsequent classification operations
3Ease of operation
If radar and camera data are fused at high level, then each source yields a decision, but the fusion occurs later in the processing pipeline
Solution Approach 1:
The patent performs preliminary fusion of radar and camera feature maps before final object detection and classification. By combining the feature maps at an early stage in the processing pipeline, the system prepares integrated information in advance, enabling faster and more accurate decision-making compared to late-stage fusion approaches
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
This approach enhances object detection accuracy and reduces computational costs by fusing raw data from both sensors at an early stage, providing more informative outputs for improved vehicle safety features like adaptive cruise control and collision avoidance.
Implementation Method 1
Radar systems utilize radio waves to determine the range, altitude, direction, and/or speed of the objects along the road. A transmitter transmits pulses of radio waves that bounce off of objects in their path. The pulses reflected from the objects return a small part of the radio wave's energy to a receiver
Data Source
AI summary
Disclosed are techniques for fusing camera and radar frames to perform object detection in one or more spatial domains. In an aspect, an on-board computer of a host vehicle receives, from a camera sensor of the host vehicle, a plurality of camera frames, receives, from a radar sensor of the host vehicle, a plurality of radar frames, performs a camera feature extraction process on a first camera frame of the plurality of camera frames to generate a first camera feature map, performs a radar feature extraction process on a first radar frame of the plurality of radar frames to generate a first radar feature map, converts the first camera feature map and/or the first radar feature map to a common spatial domain, and concatenates the first radar feature map and the first camera feature map to generate a first concatenated feature map in the common spatial domain.