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Silhouette-based Synthetic Data Generation for 3D Human Pose Estimation with a Single Wrist-mounted 360° Camera

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Citation Author(s):
Ryosuke Hori, Ryo Hachiuma, Hideo Saito, Mariko Isogawa, Dan Mikami
Submitted by:
Ryosuke Hori
Last updated:
11 October 2021 - 7:05am
Document Type:
Presentation Slides
Document Year:
2021
Event:
Presenters Name:
Ryosuke Hori
Paper Code:
2554

Abstract 

Abstract: 

In this paper, we propose a framework for 3D human pose estimation with a single 360° camera mounted on the user's wrist. Perceiving a 3D human pose with such a simple setting has remarkable potential for various applications (e.g., daily-living activity monitoring, motion analysis for sports enhancement). However, no existing work has tackled this task due to the difficulty of estimating a human pose from a single camera image in which only a part of the human body is captured and the lack of training data. Therefore, we propose an effective method for translating wrist-mounted 360° camera images into 3D human poses. We also propose silhouette-based synthetic data generation dedicated to this task, which enables us to bridge the domain gap between real-world data and synthetic data. We achieved higher estimation accuracy quantitatively and qualitatively compared with other baseline methods.

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Dataset Files

ICIP2021_paper_hori.pdf

(9)

ICIP2021_poseter_hori.pdf

(7)