
Catwalkgrader: A Catwalk Analysis and Correction System using Machine Learning and Computer Vision
Author(s) -
Tianjiao Dong,
Yu Sun
Publication year - 2021
Publication title -
machine learning and applications
Language(s) - English
Resource type - Journals
ISSN - 2394-0840
DOI - 10.5121/mlaij.2021.8303
Subject(s) - upload , computer science , grading (engineering) , artificial intelligence , machine learning , computer vision , training set , human–computer interaction , multimedia , world wide web , engineering , civil engineering
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.