New Research in Multimedia and Internet Systems

266 Pages·2015·16.5 MB·English

by  Aleksander Zgrzywa

Advances in Intelligent Systems and Computing 314
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Advances in Intelligent Systems and Computing
Volume 314
Serieseditor
JanuszKacprzyk,PolishAcademyofSciences,Warsaw,Poland
e-mail:[email protected]
AboutthisSeries
Theseries“AdvancesinIntelligentSystemsandComputing”containspublicationsontheory,
applications,anddesignmethodsofIntelligentSystemsandIntelligentComputing.Virtually
alldisciplinessuchasengineering,naturalsciences,computerandinformationscience,ICT,
economics,business,e-commerce,environment,healthcare,lifesciencearecovered.Thelist
oftopicsspansalltheareasofmodernintelligentsystemsandcomputing.
Thepublicationswithin“AdvancesinIntelligentSystemsandComputing”areprimarily
textbooksandproceedingsofimportantconferences, symposiaandcongresses.Theycover
significantrecentdevelopmentsinthefield,bothofafoundationalandapplicablecharacter.
Animportantcharacteristicfeatureoftheseriesistheshortpublicationtimeandworld-wide
distribution.Thispermitsarapidandbroaddisseminationofresearchresults.
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Chairman
NikhilR.Pal,IndianStatisticalInstitute,Kolkata,India
e-mail:[email protected]
Members
RafaelBello,UniversidadCentral“MartaAbreu”deLasVillas,SantaClara,Cuba
e-mail:[email protected]
EmilioS.Corchado,UniversityofSalamanca,Salamanca,Spain
e-mail:[email protected]
HaniHagras,UniversityofEssex,Colchester,UK
e-mail:[email protected]
LászlóT.Kóczy,SzéchenyiIstvánUniversity,Gyo˝r,Hungary
e-mail:[email protected]
VladikKreinovich,UniversityofTexasatElPaso,ElPaso,USA
e-mail:[email protected]
Chin-TengLin,NationalChiaoTungUniversity,Hsinchu,Taiwan
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JieLu,UniversityofTechnology,Sydney,Australia
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PatriciaMelin,TijuanaInstituteofTechnology,Tijuana,Mexico
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NadiaNedjah,StateUniversityofRiodeJaneiro,RiodeJaneiro,Brazil
e-mail:[email protected]
NgocThanhNguyen,WroclawUniversityofTechnology,Wroclaw,Poland
e-mail:[email protected]
JunWang,TheChineseUniversityofHongKong,Shatin,HongKong
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Moreinformationaboutthisseriesathttp://www.springer.com/series/11156
·
Aleksander Zgrzywa Kazimierz Choros´
Andrzej Siemin´ski
Editors
New Research in
Multimedia and
Internet Systems
ABC
Editors
AleksanderZgrzywa AndrzejSiemin´ski
InstituteofInformatics InstituteofInformatics
DivisionofInformationSystems DivisionofInformationSystems
WroclawUniversityofTechnology WroclawUniversityofTechnology
Wrocław Wrocław
Poland Poland
KazimierzChoros´
InstituteofInformatics
DivisionofInformationSystems
WroclawUniversityofTechnology
Wrocław
Poland
ISSN2194-5357 ISSN2194-5365 (electronic)
ISBN978-3-319-10382-2 ISBN978-3-319-10383-9 (eBook)
DOI10.1007/978-3-319-10383-9
LibraryofCongressControlNumber:2014948346
SpringerChamHeidelbergNewYorkDordrechtLondon
(cid:2)c SpringerInternationalPublishingSwitzerland2015
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Preface
MultimediaandInternettechnologiesaremoreandmoreinthehandsofthepeople.
Thistrendcallsformonographsthatdescribeboththeoreticalandpracticalaspects
ofresearchworkontheseareas.Bothaspectsarecloselyrelated.Lookingbackwe
see thatmanyideassuch as e.g. speech,face, or handwritingrecognitionhave for
longbeendeemednotfeasible.Forseveralyearstheyweremainlyresearchprojects
atuniversitiesorinresearchfacilities.Nowtheyformpartofoureverydaylife.The
pace of progressis so fast thatwe have decidedto assemble a volumethat covers
recentadvancesontheseareasthatwehavewitnessedinthelastfewyears.
Thecoveredareaisdiversebutsoareourneeds.Therefore,themonographisa
multidisciplinarywork.Some of the proposedsolutionsare so advancedthat they
maybeusedinpracticewhileothersareconcentrateduponthestudyofmorebasic
properties of Internet and multimedia data processing. In all cases the studies are
originalandwerenotpublishedanywhereelsebefore.
Thecontentofthebookhasbeendividedintofourparts:
IMultimediaInformationTechnology
IIInformationSystemSpecification
IIIInformationSystemApplications
IVWebSystemsandNetworkTechnologies
Part I consistsof 7 chapters.Itstarts with three chapterson pictureprocessing.
Theydescribea documentimagesegmentationalgorithmbasedonthe analysisof
thetiles,contentbasedindexingandretrievalofvisualdatausingtheprincipalcom-
ponent analysis (PCA) applied to spatial representationof object location, and fi-
nallythefastencodingofhuge3DdatasetsinlosslessPNGformat.Thenexttwo
chaptersareon thevideodata processing.The4thchapterexaminesthemostfre-
quentcasesoffalseandmissdetectionsintemporalsegmentationofTVsportsnews
videos.Thesegmentationisthefirststepoftheprocessforidentificationofsports
disciplinesinvideo.Inthefifthchapterthetrajectoryclusteringisusedtodiscover
differentmotion patterns and recognize eventoccurrencesin videos. The last two
chapters study the possibilities of automated human behavior recognition.One of
them focuses on the important, from a practical pointof view, task of identifying
VI Preface
thecallforhelpbehaviorwhereastheotheronthefacialemotionrecognitionusing
acascadeofneuralnetworks.
PartIIhas6chaptersandhasa moretheoreticalflavor.Thefirstchapterofthis
part is a reporton research on the predictionof real estate sales transactions. The
methodanalysesadata streamapplyingensemblesofregressionmodels.Sixself-
adapting genetic algorithms with varying mutation, crossover, and selection were
developed and tested using real-world datasets. The selection of an appropriate
methodforthepre-processingofinformationiscoveredbythenextchapter.Itap-
pliestheinformationaboutthelevelofsignalinterference.Basedonanillustrative
examplethe next chapterdescribes one of the conceptualmethodsin data mining
area that relies on the one-sided concept lattices belonging to approaches known
asFormalConceptAnalysis(FCA).ThisPartcontainsalsoareportonanattempt
torepresenta textualeventasa mixtureofsemanticstereotypesandfactualinfor-
mation.The semantic prototypesare specific for a giveneventand to define them
genericelementsareused.ThePartconcludeswithaschemaofanewapproachto
processknowledgeresourcesforlearningandtesting.Theideaistousestructured
facts, used by Google for its Knowledge Graph, in an e-learning environment to
automatesomepartsoftheeducationprocess.
Part III presents a handful of applications. It consists of six chapters. The first
ofthemdescribesanadaptiveapplicationwithanattention-gettingnameofPower
Chalk.Itwasdesignedtoresolveanimportantlimitationofcurrentdesignmethods:
adaptability.In doing so it uses the intelligentagent paradigm in order to support
scaffoldingactivities andproblemsolving.Agentsare also presentin the nextpa-
per.Theirextremelysimpleform,theantsoftheACO,areusedtosolvetheTravel-
lingSalesmenProblem.Anumberofexperimentsclearlyindicatethatthesocalled
Hyper-populatedAntColoniescouldbesuccessfullyappliedtosolveboththestatic
andthedynamicversionoftheTSP.Heuristmethodsarealsousedinthenextchap-
ter. Thistimetheyare appliedto therecognitionoftextswithvariousbackground
and foregroundcolorsevenwhen their luminosity valuesare equal. The proposed
solutionmaybeadaptedintocurrentOCRsystemsorworkasastandaloneprepro-
cessingsystem.Thelastchapterisdevotedtothetranslationofmedicaltexts.Hav-
inginmindthepopularityofinternationaltravelandhowmuchwevalueourhealth
the importance of the subject could not be understated. The research follows the
statisticalapproachtotranslationandusestheEMEAparalleltextcorporafromthe
OPUSproject.Thenextchapterisa descriptiveand predictiveanalysesofdataset
from Federal Aviation Administration (FAA) Accident/Incident Data System de-
scribingaviationaccidents.Dataminingenabledtheauthorstogeneratemodelsthat
couldbeusedasabasisforaviationwarningsystemorasasupportingmethodfor
differentprocessesrelatedtotheaviationindustry.InthelastchapterofthePartIII
theauthorsproposevisualidentitysystemforemployeesthatutilizesainformation
richgenerativelogoandgeneratesgraphicelementsofidentification.
The last fourth Part is made up of five chapters. The first two of them deal
with an analysis of Web Service Retrieval Methods and with the application of
learning algorithms to the detection of changes in group of services in SOA sys-
tem respectively. The research reported in the former encompasses the Latent
Preface VII
Semantic Indexing and modified term-document matrix. This allows the authors
to store scores for differentservice componentsseparately. In the latter one three
learningalgorithms:Kohonennetwork,emergingpatterns,andk-meansclustering
were used to detectthe anomaliesin a special modelof SOA system. The system
was designed and implemented for an experimental purpose. Then, a method of
positioningsearchresultsinmusicinformationretrievalsystemsisdescribed.Itis
basedonamodifiedversionofthePageRank.Thenextchapterdealswiththeprob-
lemoftheconfigurationofcomplexinteractiveenvironmentswhicharemadeupof
varioustypesofsensorssuchastouch,depth,orRFID.Sensorsarealsopresentin
thelastchapteronmultimediacommunicationinWirelessMultimediaSensorNet-
works(WMSN).Itpresentsthedesignoflowcomplexityschemeforobjectidenti-
ficationusingWMSN.Itsnotablefeatureislow-powerprocessingrequirementsat
thesourcemotewhileunloadingthenetworkatthesametime.
Wehopethatwehaveachievedourgoalofprovidingtheresearchercommunity
with up to date accounton work going on the diverse field of multimedia and In-
ternet data processing. We will be also pleased if the book will attract even more
scholarsto workon the areaand itwill be a source ofinspirationforthe research
communityalreadyworkingonthedomain.
Thiswouldbeourgreatestawardforourefforts.
AleksanderZgrzywa
KazimierzChoros´
AndrzejSiemin´ski
Contents
PartI: Multimedia InformationTechnology
1 DocumentImageSegmentationthroughClusteringand
ConnectivityAnalysis ........................................ 3
MihaiBogdanIlie
1.1 Introduction............................................. 3
1.2 RelatedWork............................................ 4
1.3 NewApproach .......................................... 5
1.4 ExperimentalSetup ...................................... 8
1.5 Conclusions............................................. 10
1.6 FutureResearch ......................................... 13
References.................................................... 13
2 FastEncodingofHuge3DDataSetsinLosslessPNGFormat....... 15
DanielDworak,MariaPietruszka
2.1 Introduction............................................. 15
2.2 FileFormatsforStoring3DData ........................... 16
2.2.1 PopularFileFormatsforStoring3DData ............ 16
2.2.2 FileFormatsfortheWeb .......................... 19
2.3 ProposalWayofStoring3DData........................... 20
2.3.1 ConversionfromTextPlainOBJtoTwo-Dimensional
PNG ........................................... 20
2.3.2 OBJandPNGBenchmarks ........................ 23
2.4 Conclusions............................................. 24
References.................................................... 24
3 SpatialRepresentationofObjectLocationforImageMatchingin
CBIR ...................................................... 25
TatianaJaworska
3.1 Introduction............................................. 25
3.1.1 CBIRConceptOverview .......................... 26
X Contents
3.1.2 RepresentationofGraphicalData ................... 26
3.1.3 ClassificationMethodsUsedintheCBIRSystem...... 27
3.2 SpatialRelationshipofGraphicalObjects.................... 28
3.3 ConstructionoftheSearchEngine .......................... 29
3.4 Results ................................................. 33
3.5 Conclusions............................................. 33
References.................................................... 33
4 FalseandMissDetectionsinTemporalSegmentationofTVSports
NewsVideos–CausesandRemedies ............................ 35
KazimierzChoros´
4.1 Introduction............................................. 36
4.2 RelatedWork............................................ 37
4.3 EvaluationofTemporalSegmentation ....................... 39
4.4 TemporalSegmentationandAggregationintheAVIIndexer .... 39
4.5 FalseandMissDetections ................................. 40
4.5.1 FalseDetections ................................. 40
4.5.2 MissDetections.................................. 42
4.5.3 PossibleRemedies................................ 43
4.6 ConclusionsandFurtherResearch .......................... 44
References.................................................... 45
5 AComparativeStudyofFeaturesandDistanceMetricsfor
TrajectoryClusteringinOpenVideoDomains.................... 47
ZhanhuSun,FengWang
5.1 Introduction............................................. 47
5.2 TrajectorySimilarityMeasure.............................. 48
5.2.1 Features ........................................ 48
5.2.1.1 Location............................... 48
5.2.1.2 Velocity ............................... 49
5.2.1.3 Curvature .............................. 49
5.2.1.4 Corner................................. 49
5.2.2 DistanceMetric .................................. 50
5.2.2.1 P-NormDistance........................ 50
5.2.2.2 DynamicTimeWarping(DTW)Distance ... 50
5.2.2.3 LongestCommonSubsequence(LCSS)
Distance ............................... 50
5.2.2.4 HausdorffDistance andanImproved
Version................................ 51
5.2.3 CombinationofDifferentFeatures .................. 52
5.3 TrajectoryClustering ..................................... 52
5.4 Experiments............................................. 52
5.4.1 Dataset ......................................... 52
5.4.2 EvaluationMetric ................................ 53
5.4.3 ResultsandDiscussion............................ 53