Tootfinder

PP-Motion: Physical-Perceptual Fidelity Evaluation for Human Motion Generation
Sihan Zhao, Zixuan Wang, Tianyu Luan, Jia Jia, Wentao Zhu, Jiebo Luo, Junsong Yuan, Nan Xi
https://arxiv.org/abs/2508.08179

PP-Motion: Physical-Perceptual Fidelity Evaluation for Human Motion Generation
Human motion generation has found widespread applications in AR/VR, film, sports, and medical rehabilitation, offering a cost-effective alternative to traditional motion capture systems. However, evaluating the fidelity of such generated motions is a crucial, multifaceted task. Although previous approaches have attempted at motion fidelity evaluation using human perception or physical constraints, there remains an inherent gap between human-perceived fidelity and physical feasibility. Moreover,…

AirSignatureDB: Exploring In-Air Signature Biometrics in the Wild and its Privacy Concerns
Marta Robledo-Moreno, Ruben Vera-Rodriguez, Ruben Tolosana, Javier Ortega-Garcia, Andres Huergo, Julian Fierrez
https://arxiv.org/abs/2508.08502

AirSignatureDB: Exploring In-Air Signature Biometrics in the Wild and its Privacy Concerns
Behavioral biometrics based on smartphone motion sensors are growing in popularity for authentication purposes. In this study, AirSignatureDB is presented: a new publicly accessible dataset of in-air signatures collected from 108 participants under real-world conditions, using 83 different smartphone models across four sessions. This dataset includes genuine samples and skilled forgeries, enabling a comprehensive evaluation of system robustness against realistic attack scenarios. Traditional an…

Fast adaptive tubal rank-revealing algorithm for t-product based tensor approximation
Qiaohua Liu, Jiehui Gu
https://arxiv.org/abs/2508.08557 https://arxiv…

Fast adaptive tubal rank-revealing algorithm for t-product based tensor approximation
Color images and video sequences can be modeled as three-way tensors, which admit low tubal-rank approximations via convex surrogate minimization. This optimization problem is efficiently addressed by tensor singular value thresholding (t-SVT). To mitigate the computational burden of tensor singular value decomposition (t-SVD) in each iteration, this paper introduces an adaptive randomized algorithm for tubal rank revelation in data tensors \(\mathcal{A}\). Our method selectively captures the p…

Spontaneous Hole Formation in Cell Monolayers Emerges from Collective Cell Motion
Diogo E. P. Pinto, Jan Rozman, Julia M. Yeomans
https://arxiv.org/abs/2508.06461 https://

Spontaneous Hole Formation in Cell Monolayers Emerges from Collective Cell Motion
Although cell monolayers typically remain confluent, they can spontaneously develop persistent holes as a result of collective cellular motion. Recent studies on MDCK monolayers cultured on soft substrates have revealed that cells can align to create regions of local nematic order, and topological defects that generate localised mechanical stresses which can spontaneously trigger hole formation. To investigate this process, we develop a continuum multi-phase field model that incorporates intern…

The Quiet Revolutionary of the Piano – Fauré’s Complete Piano Works Now on Piano Street https://www.pianostreet.com/blog/s…

The Quiet Revolutionary of the Piano – Fauré’s Complete Piano Works Now on Piano Street
PIANO NEWS: An article about The Quiet Revolutionary of the Piano – Fauré’s Complete Piano Works Now on Piano Street from the Piano Street Magazine.

Europe urgently needs to find and shut down all the ways by which foreign billionaires - like Trump's billionaire brigade - can influence elections here.
https://

Revealed: How foreign billionaires pump millions into British politics
The Elon Musk-shaped hole in Starmer’s Election Bill

Smartphone Exergames with Real-Time Markerless Motion Capture: Challenges and Trade-offs
Mathieu Phosanarack (LAMIH, UPHF), Laura Wallard (LAMIH, UPHF), Sophie Lepreux (LAMIH, UPHF), Christophe Kolski (LAMIH), Eug\'enie Avril (LAMIH, UPHF)
https://arxiv.org/abs/2507.06669

Smartphone Exergames with Real-Time Markerless Motion Capture: Challenges and Trade-offs
Markerless Motion Capture (MoCap) using smartphone cameras is a promising approach to making exergames more accessible and cost-effective for health and rehabilitation. Unlike traditional systems requiring specialized hardware, recent advancements in AI-powered pose estimation enable movement tracking using only a mobile device. For an upcoming study, a mobile application with real-time exergames including markerless motion capture is being developed. However, implementing such technology intro…

Dallas Cowboys 2025 rookie class' Madden NFL 26 ratings revealed https://www.si.com/nfl/cowboys/news/dallas-cowboys-2025-rookie-class-madden-nfl-26-ratings-revealed

"Wildlife activists who exposed horrific conditions at Scottish salmon farms were subjected to “Big Brother” surveillance by spies for hire working for an elite British army veteran."
https://www.theguardian.com/…

Deep Learning for Skeleton Based Human Motion Rehabilitation Assessment: A Benchmark
Ali Ismail-Fawaz, Maxime Devanne, Stefano Berretti, Jonathan Weber, Germain Forestier
https://arxiv.org/abs/2507.21018

Deep Learning for Skeleton Based Human Motion Rehabilitation Assessment: A Benchmark
Automated assessment of human motion plays a vital role in rehabilitation, enabling objective evaluation of patient performance and progress. Unlike general human activity recognition, rehabilitation motion assessment focuses on analyzing the quality of movement within the same action class, requiring the detection of subtle deviations from ideal motion. Recent advances in deep learning and video-based skeleton extraction have opened new possibilities for accessible, scalable motion assessment …