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Human motion recognition based on Nano-CMOS Image sensor.

Shangbin Li¹, Yu Liu¹

¹Physical Education Department, Harbin Engineering University, Harbin 150001, China.

Mathematical Biosciences and Engineering : MBE

|June 16, 2023

Summary

This summary is machine-generated.

This study introduces a novel human motion recognition method using Nano complementary metal-oxide-semiconductor (CMOS) image sensors. The new approach achieves high accuracy and speed for recognizing human movements in various applications.

Keywords:

Nano-CMOS Image sensor feature extraction gray image human motion recognition

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Area of Science:

Computer Vision
Sensor Technology
Biomedical Engineering

Background:

Human motion recognition is crucial for intelligent systems but current methods struggle with accuracy.
Existing techniques often yield suboptimal recognition effects, limiting their practical application.

Purpose of the Study:

To develop an improved human motion recognition method using Nano-CMOS image sensors.
To enhance the accuracy and efficiency of human motion analysis and gesture recognition.

Main Methods:

Utilized Nano-CMOS image sensors for human motion image processing and feature extraction.
Integrated background mixture models and 3D scanning features for collecting joint coordinate data.
Constructed a human motion model using sensor data and measurement matrices.
Calculated feature parameters and posterior conditional probability to obtain a recognition objective function.

Main Results:

Achieved good human motion recognition effect with high extraction accuracy.
Reported an average human motion recognition rate of 92% and high classification accuracy.
Demonstrated a recognition speed of up to 186 frames per second.

Conclusions:

The proposed Nano-CMOS based method significantly improves human motion recognition.
The high accuracy and speed make it suitable for real-time applications in intelligent monitoring and human-computer interaction.