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Root based 3D Reconstruction of Multiple Human Pose

Authors

Ayushya Rao1 and Sumer Raravikar2, 1Makers Lab, India, 2Rajiv Gandhi Infotech Park, India

Abstract

This paper explores the current landscape of 3D pose estimation methods, pivotal in virtual reality, computer-aided design, and motion capture. Focusing on transforming estimated 3D poses for virtual environments, the emphasis lies in converting pose coordinates to align with virtual avatars. A novel pipeline is proposed, converting 2D pose images into 3D humanoids in the virtual realm. Evaluation metrics include accuracy, speed, and scalability, comparing techniques to state-of-the-art methods. The paper aims to summarize findings, showcasing the potential of proposed techniques to advance 3D pose estimation in virtual environments. It serves as a valuable resource for researchers, developers, and practitioners in computer vision, AI, and virtual reality by providing a comprehensive review and experimental evaluation of 3D pose estimation and representation techniques.

Keywords

Pose Tracking,Instance Segmentation,Bio vision format,Extraction.