This thesis explores gender detection in TikTok videos through body pose analysis, utilizing deep learning models and pose estimation techniques like OpenPose. By extracting key body landmarks and analyzing their spatial relationships, the study demonstrates how pose features can effectively predict gender in social media content.
Gender Detection Using Body Pose Analysis on TikTok Videos
KARIMI, MAHYA
2024/2025
Abstract
This thesis explores gender detection in TikTok videos through body pose analysis, utilizing deep learning models and pose estimation techniques like OpenPose. By extracting key body landmarks and analyzing their spatial relationships, the study demonstrates how pose features can effectively predict gender in social media content.File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
karimi_mahya.pdf
accesso aperto
Dimensione
2.33 MB
Formato
Adobe PDF
|
2.33 MB | Adobe PDF | Visualizza/Apri |
The text of this website © Università degli studi di Padova. Full Text are published under a non-exclusive license. Metadata are under a CC0 License
Utilizza questo identificativo per citare o creare un link a questo documento:
https://hdl.handle.net/20.500.12608/86901