Human Body Detection Joint Length Estimation
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Solution Overview
Problem
Existing image analysis technologies struggle to accurately estimate the actual length between specific joints of a human body, which is crucial for enhancing the accuracy and diversity of motion data in motion detection systems.
Innovation Solution
A human body detection method that involves obtaining multiple image frames, detecting joint coordinates, determining specific postures, calculating image region heights, and estimating the actual length between joints using a combination of image capturing circuits and processors, along with pre-trained models for posture detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image analysis technology is used to detect joint coordinates and estimate actual length between joints, then motion data accuracy can be enhanced, but the measurement precision of joint lengths remains insufficient
Solution Approach 1:
The system performs preliminary actions by detecting joint coordinates and determining specific postures before estimating joint lengths. The processor identifies image frames where the human body is in specific postures (such as standing straight) and uses these predetermined posture conditions as a basis for accurate length estimation, rather than attempting to measure from arbitrary positions.
Solution Approach 2:
The system changes parameters by selecting specific image frames based on posture conditions rather than using all available frames. The processor determines whether the human body is in a specific posture (such as standing straight with feet together) and only performs length estimation on frames meeting these criteria, thereby improving measurement reliability through parameter selection.
2Measurement precision
If multiple image frames are analyzed to improve measurement accuracy, then joint length estimation can be enhanced, but the complexity of the detection system increases
Solution Approach 1:
The system segments the image frame analysis process by identifying and separating specific image frames that contain useful measurement information from other frames. The processor detects joint coordinates in multiple frames but only performs length estimation on frames where specific postures are detected, effectively segmenting the data processing workflow to reduce unnecessary computational complexity.
Solution Approach 2:
The system performs preliminary posture detection and frame selection before conducting the actual length estimation. By pre-identifying frames with specific postures (such as standing straight), the system prepares the data in advance, which simplifies the subsequent measurement process and reduces overall system complexity despite analyzing multiple frames.
3Quantity of substance
If joint coordinates are detected in all image frames, then more data is available for analysis, but the time required for processing increases
Solution Approach 1:
The system performs preliminary action by detecting joint coordinates in all image frames to gather comprehensive data, but then applies a filtering mechanism to select only specific frames for length estimation. This preliminary data collection followed by selective processing allows the system to have access to abundant data while minimizing actual processing time through intelligent frame selection.
Solution Approach 2:
The system segments the processing workload by dividing all detected joint coordinates into two categories: those from frames with specific postures (used for length estimation) and those from other frames (stored but not processed for measurement). This segmentation allows the system to maintain a large data repository while reducing the computational burden to only the necessary subset of data.
Data Source
AI summary
The invention provides a human body detection method, a human body detection device, and a computer readable storage medium. The method includes the following. A plurality of image frames related to a human body is obtained. A plurality of joint coordinates are detected in each image frame, and a plurality of specific image frames are accordingly found out. An image region height corresponding to the human body in each specific image frame is obtained. A first joint coordinate of a first joint in each specific image frame is obtained. A second joint coordinate of a second joint in each specific image frame is obtained. An actual length between the first joint and the second joint is estimated based on a height of the human body and the image region height, the first joint coordinate, and the second joint coordinate in each specific image frame.