Picture Annotation via Video Conversion for Continuous Image Sets
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Solution Overview
Problem
Manual annotation of large sets of continuous images is time-consuming and inefficient, particularly in scenarios like traffic monitoring and vehicle damage assessment, where images have slight variations due to camera movement or time delays.
Innovation Solution
Converting multiple images into a video image and performing video annotation, which allows for efficient annotation of continuous pictures by leveraging video frame correspondences to obtain annotation results for each image, thereby improving efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual annotation is performed on each picture individually, then annotation accuracy can be maintained, but annotation time and workload increase significantly
Solution Approach 1:
Multiple continuous pictures are merged into a single video file, allowing the annotation system to process them as one unified object rather than individual images. This combining approach enables the annotation algorithm to leverage temporal continuity and motion information across frames, maintaining accuracy while dramatically reducing processing time.
Solution Approach 2:
The annotation system is designed to handle both single-image annotation and video annotation modes. By implementing multi-functionality, the system can switch between processing individual pictures or batches of continuous pictures as a video, providing flexibility to adapt to different annotation scenarios and requirements.
2Productivity
If video annotation is performed on converted video images, then annotation efficiency improves significantly, but system complexity increases
Solution Approach 1:
The system architecture is segmented into distinct functional modules: a video conversion module that transforms picture batches into video format, an annotation processing module that performs the actual annotation, and a result mapping module that converts video annotation results back to individual picture annotations. This modular segmentation manages complexity by isolating each function while maintaining overall system efficiency.
Solution Approach 2:
A video file serves as an intermediary medium between the input picture batch and the annotation processing system. Instead of directly annotating multiple pictures, the system first converts them to video format, performs annotation on the video, then maps results back to original pictures. This intermediary approach simplifies the annotation process by leveraging video-specific algorithms while maintaining compatibility with picture-based workflows.
Data Source
AI summary
A picture annotation method, includes: converting, into a video image, multiple pictures in a set of pictures to be annotated; performing video annotation on the video image to obtain an annotation result; and using the obtained annotation result as an annotation result of each picture in the set of pictures to be annotated according to a correspondence between a video frame in the video image and a picture in the set of pictures to be annotated.