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MOSCHIP Action Recognition with Pose Estimation

Overview

Description

Action Recognition with pose estimation solution is developed and inferenced using RZ/V series vision MPUs with DRP-AI acceleration. This solution recognizes a person's actions with body key points from HRNet inferenced on DRP-AI. Actions were defined with certain body actions such as fallen, panic expressions, sick, eating, etc. This application can be inferenced using the RZ/V2MA vision board.

Image

Features

  • Pretrained HRnet with 80% accuracy for generating key human body points
  • Actions defined with training and test method for body key points
  • Action recognition with body points system inferenced with 90% accuracy
  • Comprehension of HRnet pose estimation key points and devise an algorithm capable of detecting actions such as falling, coughing, eating, and vomiting
  • Application for performing action recognition on an Edge AI accelerator, enabling inference of the algorithm and conducting post-processing to display outputs
  • Inference successfully performed on an Edge AI accelerator with a fast inference time of 50 ms at a speed of 10 FPS for defined actions

Comparison

Applications

  • Surveillance Camera at ATM

Documentation

Type Title Date
Product Brief PDF 448 KB
1 item