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Cloud Computing Image Processing Application in Athlete Training High-Resolution Image Detection.

Hongtao Li¹

¹Physical Education College of Xiangnan University, Chenzhou, Hunan 423000, China.

Computational Intelligence and Neuroscience

|October 13, 2022

Summary

This summary is machine-generated.

This study introduces an image detection method for athletes' motion posture analysis using depth images and bone point data. The robust system accurately predicts movement and recognizes actions, overcoming environmental interferences for real-time 3D surveillance applications.

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Area of Science:

Computer Vision
Artificial Intelligence
Internet of Things

Background:

Modern life demands advanced mobile applications, including augmented reality and AI services, on resource-limited devices.
Internet of Things (IoT) mobile applications face challenges due to the gap between demanding services and device capabilities.
Ultra-low latency and low energy consumption are critical requirements for terminal equipment in these applications.

Purpose of the Study:

To design an image detection method for athletes' motion posture prediction and action recognition.
To address the limitations of resource-demanding applications on mobile devices.
To develop a robust system for real-time 3D surveillance and motion analysis.

Main Methods:

Utilizes local image features from depth images obtained via Kinect.
Converts depth images into bone point data for analysis.
Employs a 3-stage exploration algorithm with block matching for posture prediction.
Applies Euclidean distance characteristics for movement behavior recognition.

Main Results:

The method effectively avoids interference from external factors like sun illumination.
Demonstrates excellent accuracy and robustness in predicting athlete movement postures.
Achieves reliable real-time action recognition for athletes.

Conclusions:

The developed image detection method offers high accuracy and robustness for athlete motion analysis.
Simplifies calibration tasks in 3D video surveillance.
Provides real-time inference and recognition of observed target postures with significant application value.