3D Person Behavior Estimation Using Segmented Feature Analysis
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Solution Overview
Problem
Conventional techniques fail to accurately estimate the behavior of multiple individuals in an image simultaneously.
Innovation Solution
A processing apparatus and method that generates three-dimensional feature information and person position information from time-series images, using a 3D-CNN, to estimate person behavior based on the time change of features at specific positions indicated by the person position information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional person behavior estimation techniques are used, then processing complexity is reduced, but measurement precision of multiple persons' behavior deteriorates
Solution Approach 1:
The patent segments the behavior estimation process by first detecting person positions to identify multiple individuals, then generating three-dimensional feature information specifically for each detected person's position. This segmentation allows the system to process multiple persons separately rather than as a single aggregate, improving behavior estimation accuracy for each individual while managing computational complexity through structured division of the processing task.
2Measurement precision
If three-dimensional feature information is generated for all positions, then behavior estimation accuracy is improved, but processing time increases
Solution Approach 1:
The patent extracts and focuses computational resources only on positions where persons are detected. By using person position information to identify relevant locations, the system generates three-dimensional feature information exclusively for those positions rather than processing the entire image space. This extraction approach maintains high behavior estimation accuracy for detected persons while significantly reducing processing time by eliminating unnecessary computations in empty regions.
3Productivity
If person position information is used to filter feature information, then processing efficiency is improved, but information loss occurs
Solution Approach 1:
The patent applies local quality by generating three-dimensional feature information with specific focus on the spatial and temporal characteristics of each detected person's position. Rather than uniformly processing all positions, the system adapts the feature generation to local requirements around each person, maintaining comprehensive behavioral features where needed while reducing processing in other areas. This ensures no critical behavior information is lost for detected persons while improving overall processing efficiency.
Data Source
AI summary
The present invention provides a processing apparatus (20) including a first generation unit (22) that generates, from a plurality of time-series images, three-dimensional feature information indicating a time change of a feature in each position in each of the plurality of images, a second generation unit (23) that generates person position information indicating a position in which a person is present in each of the plurality of images, and an estimation unit (24) that estimates person behavior indicated by the plurality of images, based on the time change of the feature indicated by the three-dimensional feature information in the position in which the person is present being indicated by the person position information.