CAMERA VIEW-INVARIANT MULTI-PERSON 2D HUMAN POSE ESTIMATION FOR DEPTH AND FISHEYE CAMERAS
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Date
2024-04-23
Authors
Balgabekova, Zarema
Journal Title
Journal ISSN
Volume Title
Publisher
Nazarbayev University School of Engineering and Digital Sciences
Abstract
"This world is gonna be saved by science and art, as well as curious minds and golden
hands, and open hearts...
Z, 2024
Human pose estimation is the automatic location of the human body parts from
an image or video. It is considered a prerequisite for tasks such as activity recognition
and human tracking and found its application in human-computer interaction, virtual
reality, and sign language recognition. Most of the research on human pose estimation
is concentrated on standard RGB cameras, while depth and fisheye cameras were given
much less attention due to the lack of corresponding datasets. Since fisheye and depth
cameras have several advantages over regular cameras, this project believes that it
is important to promote research on human pose estimation for these cameras and
proposes to create synthetic camera view-invariant multi-person depth and fisheye
image datasets for 2D human pose estimation. Furthermore, it is planned to train
state-of-the-art human pose estimation models on these datasets and check their
generalization on real images.
Description
Keywords
Type of access: Restricted, human pose estimation, synthetic data generation, fisheye cameras, depth images
Citation
Balgabekova, Z. (2024). Camera View-Invariant Multi-Person 2D Human Pose Estimation for Depth and Fisheye Cameras. Nazarbayev University School of Engineering and Digital Sciences