A Review of 3D Human Pose Estimation from 2D Images (CROSBI ID 696656)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Bartol, Kristijan ; Bojanić, David ; Petković, Tomislav ; D'Apuzzo, Nicola ; Pribanić, Tomislav
engleski
A Review of 3D Human Pose Estimation from 2D Images
Human pose estimation task takes images as input and extracts a set of locations representing the predefined body joints and the sparse connections between the joints, called the body parts. A pose can be estimated from single or multiple frames, in a single (monocular) or multi-view (stereo) setup and for a single person or multiple people in the scene. In this work, we provide an overview of the classic and deep learning-based 3D pose estimation approaches. We also point out relevant evaluation metrics, pose parametrizations, body models, and 3D human pose datasets. Finally, we review state-of-the-art pose estimation results, briefly discuss open problems, and propose possible future research directions.
3d computer vision ; human pose estimation ; review
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Podaci o prilogu
29
2020.
objavljeno
10.15221/20.29
Podaci o matičnoj publikaciji
Proceedings of 3DBODY.TECH 2020 11th International Conference and Exhibition on 3D Body Scanning and Processing Technologies Online/Virtual, 17-18 November 2020
D’Apuzzo , Nicola
Hometrica Consulting - Dr. Nicola D'Apuzzo
978-3-033-08209-0
Podaci o skupu
11th International Conference and Exhibition on 3D Body Scanning and Processing Technologies (3DBODY.TECH 2020)
predavanje
17.11.2020-18.11.2020
online