Skeleton Model Visualization for Overlapping Posture Recognition
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Solution Overview
Problem
Existing methods for visualizing a person's posture using a skeleton model on a two-dimensional screen can be difficult due to overlapping models and complex postures, making it hard for observers to intuitively determine the posture.
Innovation Solution
An image processing apparatus that calculates a visual recognition easiness level and adds visual features such as colors, line thickness, and transparency to the skeleton model based on three-dimensional skeleton information to enhance intuitive recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a skeleton model is displayed on a two-dimensional screen, then the posture of a person can be visualized, but the observer may find it difficult to intuitively determine the skeleton model depending on the circumstances
Solution Approach 1:
The patent applies color changes by assigning different colors to different skeleton models based on their projection overlap relationships. When skeleton models overlap on the two-dimensional screen, they are rendered in different colors to make them distinguishable. This resolves the technical contradiction by enhancing visual recognition ease through color differentiation without adding structural complexity to the display system.
Solution Approach 2:
The patent changes visual parameters such as color, line thickness, and transparency of skeleton models based on their spatial relationships and overlap conditions. By dynamically adjusting these visual parameters according to the projection state and overlap degree between models, the system improves intuitive recognition while maintaining simple line-based representation.
2Productivity
If there is a plurality of people in a captured image and a plurality of skeleton models are displayed in an overlapping manner, then all postures can be visualized simultaneously, but it may be difficult for the observer to identify the overlapping skeleton models one by one
Solution Approach 1:
The patent assigns different colors to different skeleton models based on their projection overlap relationships. When multiple skeleton models overlap on the two-dimensional screen, they are rendered in distinct colors to make them easily distinguishable. This allows the observer to identify individual models among overlapping representations without requiring complex interaction mechanisms.
Solution Approach 2:
The patent segments the visual representation by differentiating skeleton models through color coding and visual features. Each skeleton model is assigned unique visual characteristics based on its spatial relationship with other models, effectively segmenting the overlapping visual field into distinguishable entities. This segmentation enables simultaneous visualization of multiple postures while maintaining individual model identifiability.
3Measurement precision
If there is an overlap in one skeleton model because the person in the image has crossed his/her arms, then the posture can be represented accurately, but it may be difficult for the observer to determine the posture of the skeleton model
Solution Approach 1:
The patent applies different colors to different parts of the skeleton model or to multiple skeleton models representing the same person at different times. When a person's arms are crossed causing overlap, or when multiple skeleton models are displayed, color differentiation makes the overlapping structures distinguishable, helping observers accurately determine posture without confusion.
Solution Approach 2:
The patent changes visual parameters such as color, line thickness, and transparency to enhance the distinguishability of overlapping skeleton models. By adjusting these parameters based on overlap detection and spatial relationships, the system maintains accurate posture representation while improving observability of complex poses like crossed arms.
Data Source
AI summary
An image processing apparatus includes a visual recognition easiness level calculation unit and a visual feature adding unit. The visual recognition easiness level calculation unit calculates a visual recognition easiness level, the visual recognition easiness level indicating the ease of recognition of a skeleton model of a person that is built in a virtual space using three-dimensional skeleton information specifying three-dimensional coordinates of joints of the person, on a two-dimensional screen onto which the skeleton model is projected. The visual feature adding unit adds a visual feature to the skeleton model in accordance with the visual recognition easiness level.