Panoramic Image Annotation for Low-Overhead Object Detection
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Solution Overview
Problem
Existing imaging systems face challenges in efficiently generating wide field of view panoramic images and accurately annotating objects within these images, leading to redundant object detection and high computational overhead.
Innovation Solution
A method and system that combines images from multiple imaging systems to generate a panoramic image, detects objects in the panoramic image using convolutional neural networks, and annotates individual images based on the object detection in the panoramic image, reducing redundant detection and computational overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If object detection is performed on each individual image from multiple imaging systems, then comprehensive object detection coverage is achieved, but redundant detection and computational overhead increase significantly
Solution Approach 1:
The patent combines multiple individual images into a single panoramic image before performing object detection. This merging approach allows the detection algorithm to process all images collectively, identifying objects that appear across multiple views without redundant detection. The panoramic image serves as a unified representation that consolidates information from all imaging systems, thereby reducing computational overhead while maintaining comprehensive detection coverage.
2Area of stationary object
If panoramic image generation is performed to achieve wide field of view, then situational awareness is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary actions by generating the panoramic image once and storing it for subsequent object detection tasks. Rather than repeatedly generating panoramic images for each detection cycle, the system creates the panoramic representation in advance, which can then be efficiently queried for object detection. This preliminary generation approach reduces processing time for repeated operations while maintaining the wide field of view benefit.
3Measurement precision
If multiple imaging systems are used to capture images from different angles, then object detection accuracy is improved, but system complexity and data processing requirements increase
Solution Approach 1:
The patent introduces the panoramic image as an intermediary representation that consolidates data from multiple imaging systems. Instead of directly processing and coordinating multiple individual images and their respective detection results, the system uses the panoramic image as a mediator that integrates all spatial information. This intermediary approach simplifies the system architecture by providing a unified data structure for object detection, thereby reducing system complexity while preserving the accuracy benefits of multi-angle imaging.
Data Source
AI summary
Techniques for facilitating situational awareness-based annotation systems and methods are provided. In one example, a method includes receiving a respective image from each of a plurality of imaging systems. The method further includes generating a panoramic image based on the images received from the plurality of imaging devices. The method further includes detecting an object in the panoramic image. The method further includes determining, for each image received from the plurality of imaging systems, whether the image contains the object detected in the panoramic image. The method further includes annotating each image received from the plurality of imaging systems determined to contain the object to include an indication associated with the object in the image. Related systems are also provided.