{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T00:43:12Z","timestamp":1760402592177,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2021,4,2]],"date-time":"2021-04-02T00:00:00Z","timestamp":1617321600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>This paper presents a preliminary study concerning a fast preprocessing method for facial microexpression (ME) spotting in video sequences. The rationale is to detect frames containing frozen expressions as a quick warning for the presence of MEs. In fact, those frames can either precede or follow (or both) MEs according to ME type and the subject\u2019s reaction. To that end, inspired by the Adelson\u2013Bergen motion energy model and the instinctive nature of the preattentive vision, global visual perception-based features were employed for the detection of frozen frames. Preliminary results achieved on both controlled and uncontrolled videos confirmed that the proposed method is able to correctly detect frozen frames and those revealing the presence of nearby MEs\u2014independently of ME kind and facial region. This property can then contribute to speeding up and simplifying the ME spotting process, especially during long video acquisitions.<\/jats:p>","DOI":"10.3390\/jimaging7040068","type":"journal-article","created":{"date-parts":[[2021,4,2]],"date-time":"2021-04-02T10:34:09Z","timestamp":1617359649000},"page":"68","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Fast Preprocessing Method for Micro-Expression Spotting via Perceptual Detection of Frozen Frames"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3909-7463","authenticated-orcid":false,"given":"Vittoria","family":"Bruni","sequence":"first","affiliation":[{"name":"Department of Basic and Applied Sciences for Engineering, \u201cLa Sapienza\u201d Rome University, Via A. Scarpa 14-16, 00161 Rome, Italy"},{"name":"Istituto per le Applicazioni del Calcolo \u201cM. Picone\u201d, Consiglio Nazionale delle Ricerche, Via dei Taurini 19, 00185 Rome, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6088-9743","authenticated-orcid":false,"given":"Domenico","family":"Vitulano","sequence":"additional","affiliation":[{"name":"Department of Basic and Applied Sciences for Engineering, \u201cLa Sapienza\u201d Rome University, Via A. Scarpa 14-16, 00161 Rome, Italy"},{"name":"Istituto per le Applicazioni del Calcolo \u201cM. Picone\u201d, Consiglio Nazionale delle Ricerche, Via dei Taurini 19, 00185 Rome, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1007\/s00371-018-1607-6","article-title":"Micro-expression recognition: An updated review of current trends, challenges and solutions","volume":"36","author":"Goh","year":"2020","journal-title":"Vis. 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