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dc.contributor.authorDobrucali, O.en_US
dc.contributor.authorBarshan, B.en_US
dc.date.accessioned2016-02-08T09:37:48Z
dc.date.available2016-02-08T09:37:48Z
dc.date.issued2013en_US
dc.identifier.issn0010-4620
dc.identifier.urihttp://hdl.handle.net/11693/20908
dc.description.abstractThree-dimensional models of environments can be very useful and are commonly employed in areas such as robotics, art and architecture, facility management, water management, environmental/industrial/urban planning and documentation. A 3-D model is typically composed of a large number of measurements. When 3-D models of environments need to be transmitted or stored, they should be compressed efficiently to use the capacity of the communication channel or the storage medium effectively. We propose a novel compression technique based on compressive sampling applied to sparse representations of 3-D laser range measurements. The main issue here is finding highly sparse representations of the range measurements, since they do not have such representations in common domains, such as the frequency domain. To solve this problem, we develop a new algorithm to generate sparse innovations between consecutive range measurements acquired while the sensor moves. We compare the sparsity of our innovations with others generated by estimation and filtering. Furthermore, we compare the compression performance of our lossy compression method with widely used lossless and lossy compression techniques. The proposed method offers a small compression ratio and provides a reasonable compromise between the reconstruction error and processing time. © 2012 The Author 2012. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.en_US
dc.language.isoEnglishen_US
dc.source.titleComputer Journalen_US
dc.relation.isversionofhttp://dx.doi.org/10.1093/comjnl/bxs050en_US
dc.subject3-D laser range measurementen_US
dc.subject3-D modelingen_US
dc.subject3-D mappingen_US
dc.subjectCompression algorithmsen_US
dc.subjectIntelligent sensorsen_US
dc.subjectLaser range findersen_US
dc.subjectLaser range measurementsen_US
dc.subjectRobot sensing systemen_US
dc.subjectSensor systemsen_US
dc.subjectAlgorithmsen_US
dc.subjectCompressed sensingen_US
dc.subjectCompression ratio (machinery)en_US
dc.subjectData compressionen_US
dc.subjectOffice buildingsen_US
dc.subjectRobot programmingen_US
dc.subjectSensorsen_US
dc.subjectThree dimensional computer graphicsen_US
dc.subjectWater managementen_US
dc.subjectThree dimensionalen_US
dc.titleNovel compression algorithm based on sparse sampling of 3-D laser range scansen_US
dc.typeArticleen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage852en_US
dc.citation.epage870en_US
dc.citation.volumeNumber56en_US
dc.citation.issueNumber7en_US
dc.identifier.doi10.1093/comjnl/bxs050en_US
dc.publisherOxford University Pressen_US


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