Image Processing System for Multi-Action Motion Segmentation
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Solution Overview
Problem
Existing image processing techniques struggle to efficiently segment multiple actions in an image captured by a camera, despite recognizing individual actions.
Innovation Solution
An image processing system that includes an analysis unit to recognize motion images, a determination unit to assess similarity with reference motions, and a label assigning unit to segment and classify these motions based on their relation to reference motions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If individual action recognition is performed using existing techniques, then action identification is achieved, but segmentation of multiple actions in an image cannot be performed
Solution Approach 1:
The patent divides the image into multiple regions (first region and second region) and processes each region independently to identify different actions. This spatial segmentation enables the system to simultaneously recognize multiple actions within a single image, resolving the contradiction between individual action recognition accuracy and multi-action segmentation capability.
Solution Approach 2:
The patent introduces a temporal dimension by associating actions with time periods (first time period and second time period). This dimensional extension allows the system to distinguish between different actions occurring at different times, enabling both precise action identification and effective segmentation of multiple actions in the video sequence.
2Reliability
If motion segmentation is performed for each action separately, then action-specific processing is achieved, but overall processing efficiency decreases
Solution Approach 1:
The patent merges the processing of multiple actions into a unified framework where both actions are handled simultaneously through a single image division and processing pipeline. This combined approach maintains action-specific processing accuracy while significantly improving overall processing efficiency by eliminating redundant operations.
Solution Approach 2:
The patent creates a universal processing system that can handle multiple different actions through the same structural framework. The image division unit and action recognition unit are designed to process various actions uniformly, making the system multi-functional and efficient without requiring separate specialized processing pipelines for each action type.
Data Source
AI summary
An image processing system (10) includes an analysis means (11), a determination means (12), and a label assigning means (13). The analysis means (11) recognizes a plurality of motion images indicating a motion of a person from image data of motion images according to a plurality of consecutive frames obtained by capturing the person who performs a series of motions. The determination means (12) determines whether or not the motion image and a predetermined reference motion are related to each other. The label assigning means (13) assigns a label to at least some of the consecutive frames in the motion image based on the determination.