ORIGINAL RESEARCH article
Front. Psychol.
Sec. Perception Science
Volume 16 - 2025 | doi: 10.3389/fpsyg.2025.1586648
This article is part of the Research TopicUnraveling the Complexity of Sensory Space PerceptionView all 5 articles
Perception of nonrigid structures from motion using tracking image gradient vectors
Provisionally accepted
- 1Advanced Data Science Project (ADSP), RIKEN Information R&D and Strategy Headquarters (R-IH), RIKEN, Yokohama, Kanagawa, Japan
- 2Department of Information Science and Biomedical Engineering, Graduate School of Science and Engineering, Kagoshima University, Kagoshima, Japan
- 3RIKEN Center for Advanced Intelligence Project (AIP), Chuo-ku, Tokyo, Japan
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Introduction A subset of the true optical flow can be extracted by constructing a vector field that represents image gradients and then tracking vectors in this vector field. This pseudo-flow (p-flow) subset effectively visualizes nonrigid motion and leads to the perception of nonrigid structure from motion. In this study, we investigate whether the human sensory system can extract information about the physical properties of inanimate fluid, especially viscosity, from the p-flow.Methods Computer-generated movies of flowing liquid were constructed using the p-flow algorithm and the Lucas-Kanade method. The movies featured liquids of different viscosities in the form of point-light displays. The viscosity of the fluid in various subsets of these movies was then estimated by 312 participants. Results The error i.e., difference between expected and actual ratings showed smaller variabilities across repeated trials and the mean response time were significantly shorter when using the p-flow than with the conventional Lucas-Kanade method.Discussion Our results suggest that the p-flow enables a more reliable viscosity rating, which could be related to the local constraint used in the algorithm.
Keywords: optical flow, Gradient-Based Feature Tracking, Motion vector field, Perceptual Augmentation, Nonrigid structure from motion, Middle-Level Vision, Perception science
Received: 03 Mar 2025; Accepted: 23 Jul 2025.
Copyright: © 2025 Takeichi, Suzuki, Yamashita and Hiyama. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Hiroshige Takeichi, Advanced Data Science Project (ADSP), RIKEN Information R&D and Strategy Headquarters (R-IH), RIKEN, Yokohama, Kanagawa, Japan
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