# COMETH: Convex Optimization for Multiview Estimation and Tracking of Humans

## TL;DR

COMETH is a lightweight, convex optimization-based algorithm that enhances multi-view human pose estimation and tracking by integrating biomechanical constraints, improving accuracy, temporal consistency, and scalability for real-time industrial applications.

## Contribution

It introduces a novel convex optimization framework for multi-view human pose fusion that combines kinematic constraints, inverse kinematics, and state observation for improved accuracy and efficiency.

## Key findings

- Outperforms state-of-the-art methods in localization and tracking accuracy.
- Enables real-time, scalable human motion tracking in industrial settings.
- Demonstrates robustness on public and industrial datasets.

## Abstract

In the era of Industry 5.0, monitoring human activity is essential for ensuring both ergonomic safety and overall well-being. While multi-camera centralized setups improve pose estimation accuracy, they often suffer from high computational costs and bandwidth requirements, limiting scalability and real-time applicability. Distributing processing across edge devices can reduce network bandwidth and computational load. On the other hand, the constrained resources of edge devices lead to accuracy degradation, and the distribution of computation leads to temporal and spatial inconsistencies. We address this challenge by proposing COMETH (Convex Optimization for Multiview Estimation and Tracking of Humans), a lightweight algorithm for real-time multi-view human pose fusion that relies on three concepts: it integrates kinematic and biomechanical constraints to increase the joint positioning accuracy; it employs convex optimization-based inverse kinematics for spatial fusion; and it implements a state observer to improve temporal consistency. We evaluate COMETH on both public and industrial datasets, where it outperforms state-of-the-art methods in localization, detection, and tracking accuracy. The proposed fusion pipeline enables accurate and scalable human motion tracking, making it well-suited for industrial and safety-critical applications. The code is publicly available at https://github.com/PARCO-LAB/COMETH.