Catwalkgrader: A Catwalk Analysis and Correction System using Machine Learning and Computer Vision

Tianjiao Dong, Yu Sun
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Abstract

In recent years, the modeling industry has attracted many people, causing a drastic increase in the number of modeling training classes. Modeling takes practice, and without professional training, few beginners know if they are doing it right or not. In this paper, we present a real-time 2D model walk grading app based on Mediapipe, a library for real-time, multi-person keypoint detection. After capturing 2D positions of a person's joints and skeletal wireframe from an uploaded video, our app uses a scoring formula to provide accurate scores and tailored feedback to each user for their modeling skills.
猫步分级器:使用机器学习和计算机视觉的猫步分析和校正系统
近年来,模特行业吸引了很多人,导致模特培训班的数量急剧增加。建模需要练习,如果没有专业培训,很少有初学者知道他们做得对还是不对。在本文中,我们提出了一个基于Mediapipe的实时二维模型行走分级应用程序,Mediapipe是一个用于实时,多人关键点检测的库。从上传的视频中捕获一个人的关节和骨骼线框的2D位置后,我们的应用程序使用评分公式为每个用户的建模技能提供准确的分数和量身定制的反馈。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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