ANTHROPOS-V: Benchmarking the Novel Task of Crowd Volume Estimation

Luca Collorone, Stefano Darrigo, Massimiliano Pappa, Guido M. Damely di Melendugno, Giovanni Ficarra, Fabio Galasso; Proceedings of the Winter Conference on Applications of Computer Vision (WACV), 2025, pp. 5284-5294

We introduce the novel task of Crowd Volume Estimation (CVE) defined as the process of estimating the collective body volume of crowds using only RGB images. Besides event management and public safety CVE can be instrumental in approximating body weight unlocking weight-sensitive applications such as infrastructure stress assessment and assuring even weight balance. We propose the first benchmark for CVE comprising ANTHROPOS-V a synthetic photorealistic video dataset featuring crowds in diverse urban environments. Its annotations include each person's volume SMPL shape parameters and keypoints. Also we explore metrics pertinent to CVE define baseline models adapted from Human Mesh Recovery and Crowd Counting domains and propose a CVE-specific methodology that surpasses baselines. Although synthetic the weights and heights of individuals are aligned with the real-world population distribution across genders and they transfer to the downstream task of CVE from real images. Benchmark and code are available at github.com/colloroneluca/Crowd-Volume-Estimation.