{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/volumetric-reconstruction-applied-to","title":"Volumetric Reconstruction Applied to Perceptual Studies of Size and Weight","arxiv_id":"1311.2642","date":"2013-11-11","proceeding":null,"authors":["J. Balzer","M. Peters","S. Soatto"],"abstract":"We explore the application of volumetric reconstruction from structured-light\nsensors in cognitive neuroscience, specifically in the quantification of the\nsize-weight illusion, whereby humans tend to systematically perceive smaller\nobjects as heavier. We investigate the performance of two commercial\nstructured-light scanning systems in comparison to one we developed\nspecifically for this application. Our method has two main distinct features:\nFirst, it only samples a sparse series of viewpoints, unlike other systems such\nas the Kinect Fusion. Second, instead of building a distance field for the\npurpose of points-to-surface conversion directly, we pursue a first-order\napproach: the distance function is recovered from its gradient by a screened\nPoisson reconstruction, which is very resilient to noise and yet preserves\nhigh-frequency signal components. Our experiments show that the quality of\nmetric reconstruction from structured light sensors is subject to systematic\nbiases, and highlights the factors that influence it. Our main performance\nindex rates estimates of volume (a proxy of size), for which we review a\nwell-known formula applicable to incomplete meshes. Our code and data will be\nmade publicly available upon completion of the anonymous review process.","url_abs":"http://arxiv.org/abs/1311.2642v1","url_pdf":"http://arxiv.org/pdf/1311.2642v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"volumetric-reconstruction-applied-to","repo_url":"https://bitbucket.org/jbalzer/yas","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}