Multi-perspective Imaging System with Classification-Based Compression
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Solution Overview
Problem
Conventional vehicle-mounted cameras have limited perspective, field of view, and resolution, obstructing the cabin view and having limited storage, while handheld device images are often awkward and out of focus.
Innovation Solution
A multi-perspective imaging system that captures and processes images from an array of imaging devices mounted on a vehicle, performing image analysis, classification, weighting, and compression to create multi-perspective image data, providing panoramic and high-resolution imagery with intelligent storage management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple imaging devices are deployed to capture images from different perspectives, then the field of view and resolution are improved, but the storage requirements and device complexity increase
Solution Approach 1:
The system segments the image data by classification type (e.g., pedestrian, vehicle, animal, scenery) and applies different compression weights to different segments. Important objects like pedestrians and vehicles are retained with higher quality, while less critical elements are compressed more aggressively, reducing overall storage requirements while maintaining the expanded field of view benefit
Solution Approach 2:
The system dynamically changes compression parameters based on image classification results. By adjusting compression ratios and quality levels according to the importance of detected objects, the system optimizes the balance between storage efficiency and image quality across the multi-perspective imaging array
2Manufacturing precision
If multiple imaging devices are deployed to capture images from different perspectives, then the resolution and perspective coverage are improved, but the device complexity increases
Solution Approach 1:
The system merges multiple images from different imaging devices into a unified multi-perspective dataset. By combining the computational resources and processing pipelines, the system manages the complexity of coordinating multiple high-resolution cameras while achieving enhanced perspective coverage and resolution through intelligent image fusion and classification
Solution Approach 2:
The imaging system is designed with multi-functionality to handle various object types (pedestrians, vehicles, animals, scenery) and various modes (panoramic viewing, object detection, compression optimization). This universal design approach manages device complexity by creating a flexible platform that can adapt to different imaging scenarios without requiring separate specialized systems
3Device complexity
If conventional vehicle-mounted cameras are used, then the device simplicity is maintained, but the field of view and resolution are limited
Solution Approach 1:
The system transitions from a single-camera viewpoint to multi-dimensional perspective capture by deploying imaging devices at multiple locations on the vehicle (front, rear, sides). This dimensional expansion of the imaging architecture dramatically increases the field of view and provides comprehensive panoramic coverage while managing complexity through systematic arrangement and classification-based processing
Data Source
AI summary
A system includes a processor to capture a first image of a scene by a first imaging device of the array of imaging devices, capture a second image of the scene by a second imaging device of the array of imaging devices, perform image analysis of the first image and the second image and determining that an object is present in the first image and the object is present in the second image, the first image representing a first perspective of the object and the second image representing a second perspective of the object different from the first perspective of the object, classify the object with a classification based on a list of known objects and weight an object portion of the first image and an object portion of the second image based on the classification, compress the first image and the second image based on the weighting, encode the first image and the second image as multi-perspective image data, and store the multi-perspective image data in the non-transitory computer-readable medium based on the classification.