Paper ID | MLR-APPL-IVASR-6.4 | ||
Paper Title | SILHOUETTE-BASED SYNTHETIC DATA GENERATION FOR 3D HUMAN POSE ESTIMATION WITH A SINGLE WRIST-MOUNTED 360° CAMERA | ||
Authors | Ryosuke Hori, Ryo Hachiuma, Hideo Saito, Keio University, Japan; Mariko Isogawa, Dan Mikami, NTT, Japan | ||
Session | MLR-APPL-IVASR-6: Machine learning for image and video analysis, synthesis, and retrieval 6 | ||
Location | Area D | ||
Session Time: | Wednesday, 22 September, 08:00 - 09:30 | ||
Presentation Time: | Wednesday, 22 September, 08:00 - 09:30 | ||
Presentation | Poster | ||
Topic | Applications of Machine Learning: Machine learning for image & video analysis, synthesis, and retrieval | ||
IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
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. |