The integration of multi-view imaging and pose estimation represents a significant advance in computer vision applications, offering new possibilities for understanding human movement and interactions. This work presents a new algorithm that improves multi-view multi-person pose estimation, focusing on fast triangulation speeds and good generalization capabilities. The approach extends to whole-body pose estimation, capturing details from facial expressions to finger movements across multiple individuals and viewpoints. Adaptability to different settings is demonstrated through strong performance across unseen datasets and configurations. To support further progress in this field, all of this work is publicly accessible.

翻译：多视角成像与姿态估计的融合代表了计算机视觉应用领域的重大进展，为理解人体运动与交互提供了新的可能性。本研究提出了一种改进多视角多人姿态估计的新算法，重点在于实现快速的三角测量速度与良好的泛化能力。该方法可扩展至全身姿态估计，能够捕捉从面部表情到手指动作的细节，适用于多个个体及不同视角。通过在未见过的数据集和配置上展现出的强大性能，证明了该方法对不同场景的适应性。为支持该领域的进一步发展，本工作的全部内容均已公开。