Edoardo Marchetti
3DYogaSeg: A New Dataset and Benchmark for Skeleton-Based Action Recognition and Segmentation in yoga videos.
Rel. Giuseppe Bruno Averta, Chiara Plizzari. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024
|
Preview |
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (7MB) | Preview |
Abstract
In recent years, the popularity of online platforms for home exercise programs, particularly yoga, has increased significantly. Yoga involves various poses, known as "asanas", where small differences can change the name and nature of the exercise. However, many video tutorials do not have accurate names or descriptions for these poses, which presents a challenge for beginners. Automated tools for identifying yoga poses offer critical support for users approaching these sessions. Although there is a vast literature on understanding videos, there is a significant gap in the recognition of specific exercises in yoga videos, largely due to a lack of adequate datasets.
To solve this problem, we introduced a new dataset to identify and segment yoga poses using skeletal data
Relatori
Anno Accademico
Tipo di pubblicazione
Numero di pagine
Corso di laurea
Classe di laurea
Aziende collaboratrici
URI
![]() |
Modifica (riservato agli operatori) |
