IMUOptimize: A Data-Driven Approach to Optimal IMU Placement for Human Pose Estimation with Transformer Architecture

no code implementations • 14 Feb 2024 • Varun Ramani, Hossein Khayami, Yang Bai, Nakul Garg, Nirupam Roy

This paper presents a novel approach for predicting human poses using IMU data, diverging from previous studies such as DIP-IMU, IMUPoser, and TransPose, which use up to 6 IMUs in conjunction with bidirectional RNNs.

Pose Estimation Time Series +1