Search results for "Multimedia"

showing 10 items of 692 documents

Multiple Structured Light-Based Depth Sensors for Human Motion Analysis: A Review

2012

Human motion analysis is an increasingly important active research domain with various applications in surveillance, human-machine interaction and human posture analysis. The recent developments in depth sensor technology, especially with the release of the Kinect device, have attracted significant attention to the question of how to take advantage of this technology in order to achieve accurate motion tracking and action detection in marker-less approaches. In this paper, we review the benefits and limitations deriving from the adoption of structured light-based depth sensors in human motion analysis applications. Surveying the relevant literature, we have identified in calibration, interf…

[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM]Computer sciencebusiness.industry[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHuman Motion Analysis020207 software engineering02 engineering and technologyInterference (wave propagation)Human motionDomain (software engineering)Match movingMultiple depth sensorsCalibration0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionBias correctionArtificial intelligenceInterferencebusinessComputingMilieux_MISCELLANEOUSStructured light[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]
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Evolutionary-based 3D reconstruction using an uncalibrated stereovision system: application of building a panoramic object view

2010

In this paper, we propose an original evolutionary-based method for 3D panoramic reconstruction from an uncalibrated stereovision system (USS). The USS is composed of five cameras located on an arc of a circle around the object to be analyzed. The main originality of this work concerns the process of the calculation of the 3D information. Actually, with our method, 3D coordinates are directly obtained without any prior estimation of the fundamental matrix. The method operates in two steps. Firstly, points of interest are detected in pairs of images acquired by two consecutive cameras of the USS are matched. And secondly, using evolutionary algorithms, we jointly compute the transformed matr…

[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM]Object viewComputer Networks and CommunicationsComputer sciencebusiness.industry3D reconstruction[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]020207 software engineering02 engineering and technologyHardware and Architecture0202 electrical engineering electronic engineering information engineeringMedia Technology020201 artificial intelligence & image processingComputer visionArtificial intelligenceFundamental matrix (computer vision)businessSoftwareComputingMilieux_MISCELLANEOUS[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]
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MEDES '10: International ACM Conference on Management of Emergent Digital EcoSystems, Bangkok, Thailand, October 26-29, 2010

2010

International audience

[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-WB] Computer Science [cs]/Web[INFO.INFO-WB]Computer Science [cs]/Web[ INFO.INFO-WB ] Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM][SCCO.COMP]Cognitive science/Computer science[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][SCCO.COMP] Cognitive science/Computer science[ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]ComputingMilieux_MISCELLANEOUS[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]
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Rules, Photos, and Crowdsourcing for Relationship Type Discovery in Social Networks

2011

International audience

[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-WB] Computer Science [cs]/Web[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer science[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][SCCO.COMP] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]ComputingMilieux_MISCELLANEOUS[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]
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MEDES '11: International ACM Conference on Management of Emergent Digital EcoSystems, San Francisco, CA, USA, November 21-24, 2011

2011

International audience

[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-WB] Computer Science [cs]/Web[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer science[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][SCCO.COMP] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]ComputingMilieux_MISCELLANEOUS[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]
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Special issue on context-aware and mobile multimedia databases and services

2010

International audience

[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-WB] Computer Science [cs]/Web[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer science[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][SCCO.COMP] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]ComputingMilieux_MISCELLANEOUS[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]
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Adding Knowledge Extracted by Association Rules into Similarity Queries

2010

International audience; In this paper, we propose new techniques to improve the quality of similarity queries over image databases performing association rule mining over textual descriptions and automatically extracted features of the image content. Based on the knowledge mined, each query posed is rewritten in order to better meet the user expectations. We propose an extension of SQL aimed at exploring mining processes over complex data, generating association rules that extract semantic information from the textual description superimposed to the extracted features, thereafter using them to rewrite the queries. As a result, the system obtains results closer to the user expectation than i…

[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-WB] Computer Science [cs]/Web[INFO.INFO-WB]Computer Science [cs]/Webuser expectation[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer scienceInformationSystems_DATABASEMANAGEMENTsimilarity queriescontent-based retrievalassociation rules[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][SCCO.COMP] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB][INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]SQL extensionquery rewriting[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]
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Identifying Algebraic Properties to Support Optimization of Unary Similarity Queries

2009

International audience; Abstract. Conventional operators for data retrieval are either based on exact matching or on total order relationship among elements. Neither ofthem is appropriate to manage complex data, such as multimedia data, time series and genetic sequences. In fact, the most meaningful way tocompare complex data is by similarity. However, the Relational Algebra, employed in the Relational Database Management Systems (RDBMS),cannot express similarity criteria. In order to address this issue, we provide here an extension of the Relational Algebra, aimed at representingsimilarity queries in algebraic expressions. This paper identies fundamental properties to allow the integration…

[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-WB] Computer Science [cs]/Websimilarity algebra[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer sciencealgebraic properties[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][SCCO.COMP] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]query optimiza-tion[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]unary similarity queries[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]
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Spatial Rules through Spatial Rule built-ins in SWRL

2010

International audience; The paper presents a method to include spatial rule within rule languages like SWRL to infer spatial rules within semantic web framework. The concept presented here could benefit both geospatial community as they benefit using the adjusted knowledge base to infer spatial rule and semantic web community as the inclusion of spatial data in its framework

[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-WB] Computer Science [cs]/Web[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-WB ] Computer Science [cs]/WebSpatial data[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Knowledge ManagementInference Rules[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Geospatial AnalysisJGRCS[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]Semantic Web
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Automatic and Adaptive Fitting of the Cochlear Implant by Using Interactive Evolutionary Algorithms

2011

International audience

[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]ComputingMilieux_MISCELLANEOUS[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]
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