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

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.

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