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Multimedia Database Management System. Wei Tsang Ooi CS731. MMDBMS : Querying Interface, Indexing and Buffer Management. Why MMDBMS ? . Concurrency Control Recovery Privacy Query Support Version Control. Example of MMDBMS . Digital Library News-On-Demand Video-On-Demand
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Multimedia Database Management System Wei Tsang Ooi CS731
Why MMDBMS ? • Concurrency Control • Recovery • Privacy • Query Support • Version Control
Example of MMDBMS • Digital Library • News-On-Demand • Video-On-Demand • Music Database • Telemedicine • Geographic Information System
000003 000002 000004 000001 600M 530M 450M 510M 30 30 30 30 parag tibor soam wei l5.mpg l4.mpg l6.mpg l7.mpg No Intergration id size fps title filename
Semi-intergrated BLOB 000001b70ae9902...
Fully Intergrated index buffers storage
Nature of Multimedia Data • Large amount of data • Time sensitive • Vague matching
Database Components Query Interface Query Processing storage manager buffer manager index
Problems • Needs support for : • temporal and spatial relations • “natural” interface • fuzzy query • SQL is not suitable.
13 Temporal Relations • Allen 83 starts before equals meets during overlaps finished by finishes overlapped by contains met by started by after
Spatio Relations • Papadias, Theodoridis 96 • Topological Relations • Directional Relations
disjoint meet overlap covered by inside equal covers contains Topological Relations
Directional Relations North NW NE West East SW SE South
Spatio-temporal Relations • overlap-after • meet-during • ...
Querying • Image • Audio • Music • Sound • Speech • Video
Querying Image • Common approach • allow query by sketches (color, shape, texture) or examples. • perform matching by Feature Vectors F = (v1, v2, ... vn) • e.g. Color Histogram
Querying Image • Exisiting Systems : • QBIC • VisualSEEK • PhotoBook • Virage • FourEyes
Querying Music • Hawley 93 • Input by MIDI Keyboard • Measure relative pitch (U, D, S) • Perform exact match with existing database.
Querying Music • Ghias, Logan, Chamberlin & Smith 95 • Input by humming • Extract relative pitch • Perform approximate matching
Querying Music • Chou, Chen, & Liu 96 • Query by chord • Represents musics by chord • C Am Em F C Am Em F ... • Perform fuzzy match
Querying Music • Chen & Chen 98 • Query by “rhythm” (tempo ?) • Represents musics by rhythm • | ¶¶— | ¶·¶·| ¶¶¶¶ | ... • Perform fuzzy match
Querying Sound • Wold, Blum, Keisar & Wheaton 96 • Analyze audio to extract features • loudness, pitch, brightness, bandwidth and harmonicity • Segment the audio to pieces • Feature Vector Matchings
Querying Speech • Hauptmann & Witbrock 97 • Informedia • Use speech recorgnition to convert audio to text • segment audio using silence detection • Query by speaking keywords
Querying Video • Query by speech • Informedia • Visual approach • VideoQ
VideoQ • Chang et. al 97 • User can sketch objects • Specifies • color • texture • shape • motion • duration • camera zoom and pan.
VisualQ Example Titanic Sinking Someone Skiing
Indexing • Requirements • support spatio-temporal operations • support fuzzy matches
Indexing Images • N-dimentional indices for feature vector • Well studied in DB/CG community • Two examples : • VP-tree • R-tree
VP-tree R Q P PQS VWTU R T S U W V
VP-tree R Q P U R P T S S Q T VW U W V
Indexing Audio • Audio are modeled as strings • Inexact match is needed • Common indices for string search can be used • Example • PAT-tree
PAT-tree ab b c abc c abc c ababc abc babc bc c
Indexing Video • Treat time as third dimension • We can use any multidimension indexing structures
Buffer Management • Minimizing response time • Ensuring continuity and synchronization • Prefetching & Replacement
Glossaries • Presentation • Media Stream • Media Object
Buffer Management • Relevance Based • Distance Based • Buffer Consumption
Relevance Based • Moser, Kraiß & Klas 95 : L/MRP • Definition: • State = (curr obj, skip) • Relevance : State Real
Relevance Based • Prefetch : • future objects with highest relevance • Replace : • old objects with lowest relevance
Example (5,+2) Relevance History Referenced Skip Time Scale
Distance Based • Özden, Rastogi & Silberschatz 96 • Definition • distance of a client C is the offset between C and the immediate following client.
Distance Based • Replace : • blocks consumed by clients with largest distance
Example C1 C2 C3 C4
Example C1 C2 C3 C4
Example C1 C2 C3 C4
Buffer Consumption • Wu & Yu 97 • Definition : • Buffer consumption = amount of buffer used x total time