Vehicle Damage Heat Map via 3D Point Cloud Alignment
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Solution Overview
Problem
Current image processing systems are unable to quickly and effectively detect changes in objects, such as damage to vehicles or buildings, due to difficulties in comparing images from different perspectives, angles, and camera distortions, leading to inaccurate or incomplete change detection.
Innovation Solution
An image processing system that compares a base object model with target images using landmarks and correction filters to align and correct for camera distortions, followed by statistical processing with convolutional neural networks to quantify changes and display them as a heat map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If images are compared from different perspectives and angles, then more comprehensive object coverage is achieved, but image alignment accuracy deteriorates
Solution Approach 1:
The patent transitions from 2D image comparison to 3D point cloud representation. By capturing spatial coordinates (x, y, z) of landmarks and transforming them into a common reference frame, the system achieves accurate alignment across multiple viewpoints while maintaining precise measurements. The 3D spatial transformation allows comprehensive object coverage from different angles without sacrificing alignment accuracy.
Solution Approach 2:
The patent introduces a reference frame and transformation matrices as intermediaries between images taken from different perspectives. These mathematical tools serve as mediators that coordinate the spatial relationships between multiple views, enabling accurate alignment while maintaining comprehensive object coverage across different angles and distances.
2Difficulty of detecting and measuring
If statistical processing techniques are used to detect features, then feature detection capability is improved, but change detection capability deteriorates
Solution Approach 1:
The patent segments the object into distinct landmarks and divides the analysis into two phases: first using statistical processing to detect and identify landmarks, then using precise coordinate measurement and transformation to detect changes. This segmentation allows the system to leverage the strengths of statistical methods for feature detection while maintaining precision for change measurement through coordinate-based comparison in a reference frame.
3Measurement precision
If multiple cameras are used to reduce distortions, then image accuracy is improved, but system complexity deteriorates
Solution Approach 1:
The patent creates a digital 3D copy (point cloud) of the object that serves as a reference model. This virtual replica captures the object's geometry and can be transformed and compared without requiring multiple physical cameras. The digital copy approach achieves accurate change detection while avoiding the complexity of multi-camera hardware systems.
4Productivity
If simple image comparison is performed, then processing speed is improved, but change detection accuracy deteriorates
Solution Approach 1:
The patent extracts key landmarks and their coordinate information from the images, separating the essential change-detection data from the full image content. By working with extracted landmark coordinates rather than complete images, the system achieves fast processing speeds while maintaining high change detection accuracy through precise coordinate transformation and comparison in a reference frame.
Data Source
AI summary
An image processing system and/or method obtains source images in which a damaged vehicle is represented, and performs image processing techniques to determine, predict, estimate, and/or detect damage that has occurred at various locations on the vehicle. The image processing techniques may include generating a composite image of the damaged vehicle, aligning and/or isolating the image, applying convolutional neural network techniques to the image to generate damage parameter values, where each value corresponds to damage in a particular location of vehicle, and/or other techniques. Based on the damage values, the image processing system/method generates and displays a heat map for the vehicle, where each color and/or color gradation corresponds to respective damage at a respective location on the vehicle. The heat map may be manipulatable by the user, and may include user controls for displaying additional information corresponding to the damage at a particular location on the vehicle.