Tootfinder

Detecting In-Person Conversations in Noisy Real-World Environments with Smartwatch Audio and Motion Sensing
Alice Zhang, Callihan Bertley, Dawei Liang, Edison Thomaz
https://arxiv.org/abs/2507.12002

Detecting In-Person Conversations in Noisy Real-World Environments with Smartwatch Audio and Motion Sensing
Social interactions play a crucial role in shaping human behavior, relationships, and societies. It encompasses various forms of communication, such as verbal conversation, non-verbal gestures, facial expressions, and body language. In this work, we develop a novel computational approach to detect a foundational aspect of human social interactions, in-person verbal conversations, by leveraging audio and inertial data captured with a commodity smartwatch in acoustically-challenging scenarios. To…

Fundamental diagram constrained dynamic optimal transport via proximal splitting methods
Anqi Dong, Karl Henrik Johansson, Johan Karlsson
https://arxiv.org/abs/2507.20717 https:…

Fundamental diagram constrained dynamic optimal transport via proximal splitting methods
Optimal transport has recently been brought forward as a tool for modeling and efficiently solving a variety of flow problems, such as origin-destination problems and multi-commodity flow problems. Although the framework has shown to be effective for many large scale flow problems, the formulations typically lack dynamic properties used in common traffic models, such as the Lighthill-Whitham-Richards model. In this work, we propose an optimal transport framework that includes dynamic constraint…