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Article: Block-wise motion detection using compressive imaging system
Title | Block-wise motion detection using compressive imaging system |
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Authors | |
Keywords | Compressive imaging Feature-specific imaging Motion detection Gaussian mixture model Tracking |
Issue Date | 2011 |
Publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/optcom |
Citation | Optics Communications, 2011, v. 284 n. 5, p. 1170-1180 How to Cite? |
Abstract | A block-wise motion detection strategy based on compressive imaging, also referred to as feature-specific imaging (FSI), is described in this work. A mixture of Gaussian distributions is used to model the background in a scene. Motion is detected in individual object blocks using feature measurements. Gabor, Hadamard binary and random binary features are studied. Performance of motion detection methods using pixel-wise measurements is analyzed and serves as a baseline for comparison with motion detection techniques based on compressive imaging. ROC (Receiver Operation Characteristic) curves and AUC (Area Under Curve) metrics are used to quantify the algorithm performance. Because a FSI system yields a larger measurement SNR (Signal-to-Noise Ratio) than a traditional system, motion detection methods based on the FSI system have better performance. We show that motion detection algorithms using Hadamard and random binary features in a FSI system yields AUC values of 0.978 and 0.969 respectively. The pixel-based methods are only able to achieve a lower AUC value of 0.627. © 2010 Elsevier B.V. All rights reserved. |
Persistent Identifier | http://hdl.handle.net/10722/139225 |
ISSN | 2023 Impact Factor: 2.2 2023 SCImago Journal Rankings: 0.538 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Ke, J | en_US |
dc.contributor.author | Ashok, A | en_US |
dc.contributor.author | Neifeld, MA | en_US |
dc.date.accessioned | 2011-09-23T05:47:23Z | - |
dc.date.available | 2011-09-23T05:47:23Z | - |
dc.date.issued | 2011 | en_US |
dc.identifier.citation | Optics Communications, 2011, v. 284 n. 5, p. 1170-1180 | en_US |
dc.identifier.issn | 0030-4018 | - |
dc.identifier.uri | http://hdl.handle.net/10722/139225 | - |
dc.description.abstract | A block-wise motion detection strategy based on compressive imaging, also referred to as feature-specific imaging (FSI), is described in this work. A mixture of Gaussian distributions is used to model the background in a scene. Motion is detected in individual object blocks using feature measurements. Gabor, Hadamard binary and random binary features are studied. Performance of motion detection methods using pixel-wise measurements is analyzed and serves as a baseline for comparison with motion detection techniques based on compressive imaging. ROC (Receiver Operation Characteristic) curves and AUC (Area Under Curve) metrics are used to quantify the algorithm performance. Because a FSI system yields a larger measurement SNR (Signal-to-Noise Ratio) than a traditional system, motion detection methods based on the FSI system have better performance. We show that motion detection algorithms using Hadamard and random binary features in a FSI system yields AUC values of 0.978 and 0.969 respectively. The pixel-based methods are only able to achieve a lower AUC value of 0.627. © 2010 Elsevier B.V. All rights reserved. | - |
dc.language | eng | en_US |
dc.publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/optcom | - |
dc.relation.ispartof | Optics Communications | en_US |
dc.rights | NOTICE: this is the author’s version of a work that was accepted for publication in Optics Communications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Optics Communications, 2011, v. 284 n. 5, p. 1170-1180. DOI: 10.1016/j.optcom.2010.11.028 | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Compressive imaging | - |
dc.subject | Feature-specific imaging | - |
dc.subject | Motion detection | - |
dc.subject | Gaussian mixture model | - |
dc.subject | Tracking | - |
dc.title | Block-wise motion detection using compressive imaging system | en_US |
dc.type | Article | en_US |
dc.identifier.email | Ke, J: junke@eee.hku.hk | en_US |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1016/j.optcom.2010.11.028 | - |
dc.identifier.scopus | eid_2-s2.0-78751641943 | - |
dc.identifier.hkuros | 192220 | en_US |
dc.identifier.volume | 284 | en_US |
dc.identifier.issue | 5 | - |
dc.identifier.spage | 1170 | en_US |
dc.identifier.epage | 1180 | en_US |
dc.identifier.isi | WOS:000287179500010 | - |
dc.publisher.place | Netherlands | - |
dc.identifier.citeulike | 8341375 | - |
dc.identifier.issnl | 0030-4018 | - |