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dc.contributor.authorTu, Zhengzhengen_UK
dc.contributor.authorZheng, Aihuaen_UK
dc.contributor.authorYang, Erfuen_UK
dc.contributor.authorLuo, Binen_UK
dc.contributor.authorHussain, Amiren_UK
dc.description.abstractIn the human brain, independent components of optical flows from the medial superior temporal area are speculated for motion cognition. Inspired by this hypothesis, a novel approach combining independent component analysis (ICA) with principal component analysis (PCA) is proposed in this paper for multiple moving objects detection in complex scenes—a major real-time challenge as bad weather or dynamic background can seriously influence the results of motion detection. In the proposed approach, by taking advantage of ICA’s capability of separating the statistically independent features from signals, the ICA algorithm is initially employed to analyze the optical flows of consecutive visual image frames. As a result, the optical flows of background and foreground can be approximately separated. Since there are still many disturbances in the foreground optical flows in the complex scene, PCA is then applied to the optical flows of foreground components so that major optical flows corresponding to multiple moving objects can be enhanced effectively and the motions resulted from the changing background and small disturbances are relatively suppressed at the same time. Comparative experimental results with existing popular motion detection methods for challenging imaging sequences demonstrate that our proposed biologically inspired vision-based approach can extract multiple moving objects effectively in a complex scene.en_UK
dc.relationTu Z, Zheng A, Yang E, Luo B & Hussain A (2015) A Biologically Inspired Vision-Based Approach for Detecting Multiple Moving Objects in Complex Outdoor Scenes. Cognitive Computation, 7 (5), pp. 539-551.
dc.rightsThe publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.en_UK
dc.subjectMotion cognitionen_UK
dc.subjectOptical flowen_UK
dc.subjectIndependent component analysisen_UK
dc.subjectPrincipal component analysisen_UK
dc.subjectMoving objects detectionen_UK
dc.titleA Biologically Inspired Vision-Based Approach for Detecting Multiple Moving Objects in Complex Outdoor Scenesen_UK
dc.typeJournal Articleen_UK
dc.rights.embargoreason[Tu et al_Cogn Comput_2015.pdf] The publisher does not allow this work to be made publicly available in this Repository therefore there is an embargo on the full text of the work.en_UK
dc.citation.jtitleCognitive Computationen_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderEngineering and Physical Sciences Research Councilen_UK
dc.contributor.affiliationAnhui Universityen_UK
dc.contributor.affiliationAnhui Universityen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationAnhui Universityen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.relation.funderprojectDual Process Control Models in the Brain and Machines with Application to Autonomous Vehicle Controlen_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
local.rioxx.authorTu, Zhengzheng|en_UK
local.rioxx.authorZheng, Aihua|en_UK
local.rioxx.authorYang, Erfu|en_UK
local.rioxx.authorLuo, Bin|en_UK
local.rioxx.authorHussain, Amir|0000-0002-8080-082Xen_UK
local.rioxx.projectEP/I009310/1|Engineering and Physical Sciences Research Council|
local.rioxx.filenameTu et al_Cogn Comput_2015.pdfen_UK
Appears in Collections:Computing Science and Mathematics Journal Articles

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