{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T15:31:15Z","timestamp":1781105475460,"version":"3.54.1"},"reference-count":0,"publisher":"IGI Global Scientific Publishing","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,7,1]]},"abstract":"<p>The brain visual cortical simple cells have strong response to notable edges with directivity and contrast of light and dark, as well as the non-classical receptive fields of the neurons in visual cortex that have inhibition function to small light-spot stimulation. Because of this property, human vision system contrast sensitivity tends to dynamic videos. This paper, based on biological visual features, constructs an energy-computing model for dynamic video behaviors analysis, and designs computing methods for strengthening selectivity to directions of edges and inhibiting energy of non-significant areas in the images. The experiment is conducted on 30,000 frames of dynamic behaviors in video and shows 90% accuracy, which proves that the proposed method is capable to simulate the function of visual cortex simple cells, i.e. the enhancement to directional selection, and the inhabitation function of non-classical receptive fields, as well as extract energy features of dynamic behaviors in video. This contributes a choice for computer image processing and improves the understanding of machine vision.<\/p>","DOI":"10.4018\/ijcini.2014070101","type":"journal-article","created":{"date-parts":[[2015,6,17]],"date-time":"2015-06-17T12:59:39Z","timestamp":1434545979000},"page":"1-12","source":"Crossref","is-referenced-by-count":2,"title":["An Energy Computing Method Inspired from Visual Cognitive Function for Dynamic Behavioural Detection in Video Frames"],"prefix":"10.4018","volume":"8","author":[{"given":"Zuojin","family":"Li","sequence":"first","affiliation":[{"name":"Chongqing University of Science and Technology, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Peng","sequence":"additional","affiliation":[{"name":"Chongqing University of Science and Technology, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liukui","family":"Chen","sequence":"additional","affiliation":[{"name":"Chongqing University of Science and Technology, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Gui","sequence":"additional","affiliation":[{"name":"Chongqing University of Science and Technology, Chongqing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Computing, Unitec Institute of Technology, Mount Albert, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","container-title":["International Journal of Cognitive Informatics and Natural Intelligence"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=130767","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T18:55:52Z","timestamp":1654109752000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJCINI.2014070101"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2014,7,1]]},"references-count":0,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2014,7]]}},"URL":"https:\/\/doi.org\/10.4018\/ijcini.2014070101","relation":{},"ISSN":["1557-3958","1557-3966"],"issn-type":[{"value":"1557-3958","type":"print"},{"value":"1557-3966","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,7,1]]}}}