the automatic generation of formal annotations in a multimedia indexing and searching environment...

The Automatic Generation of Formal Annotations in a MultiMedia Indexing and Searching Environment

Thierry DeclerckDFKI GmbH

Annotation Workshop, DI, 15. Februar 2002

The MUMIS Consortium

• CTIT University of Twente, Enschede, NL NLP/IE• TSI University of Nijmegen, Nijmegen, NL

ASR• DFKI Saarbrücken, D

NLP/IE• MPI Nijmegen, NL MM

Archives• DCS University of Sheffield, UK NLP/IE• ESTEAM Gothenburg, SE (location Athens, GR)

Translation Software

• VDA Hilversum, NL Video

Objectives of MUMIS

• Technology development to automatically index (with formal annotations) lengthy multimedia recordings (off-line process)

Find and annotate relevant events, together with the involved entities and relations. Also detect Metadata information.

• Technology development to exploit indexed multimedia archives (on-line process)

Search for interesting scenes and play them via Internet

Test Domain: Soccer Games / UEFA Tournament 2000

Off-line Task

Indexing by

• Automatic Speech Recognition (Radio/TV Broadcasts)

Automatically transforms the speech signals into texts (for 3 languages — Dutch, English and German)

• Natural Language Processing (Information Extraction)

Analyse all available textual documents (newspapers, speech transcripts, tickers, formal texts ...), identify and extract interesting entities, relations and events. Also detect Metadata information.

• Merging all the annotations produced so far• Create a database with formal annotations• Use video processing to adjust time marks

Gain

• What gets lost? Is it necessary?• Potential: direct Internet Service, less

dependencies

Current Procedure MUMIS Procedure

Manual Video Annotation Automatic Video Annotation and DB

IntegrationIntegration Central DB

Query via PC Query via PC

Results on PC

Results on PCAnd

Select & Play

Contact Video Archive

Get Video Tapes

Search on Tape on VCR

Segment & Play

The Generation of Formal Annotations

• Metadata (type of game, teams, date, final score, players etc.), as they can be used a.o. for classifying and filtering videos in the MM digital archive• Events (particular actions with time codes, involved entities and related events), as they can be extracted from the video sequences• All Formal Annotations available in XML Standard

The Event TableRelated to domain ontology and multilingual terminology. Guiding the generation of formal annotations

Final whistle # 90>t>120

Subj=referee, score etc… Final score

Shot on Goal # 0>t>120

Subj=pl, loc=loc, cons=cons,..

Dribbling # 0>t>120

Subj=pl, loc=loc, …

Substitution # 0>t>120

Subj=pl, I.obj=pl, cause=c, …

Team (adding pl)

Red Card # 0>t>120

Subj=ref, I.obj=pl, cause=c, …

Team (red at t)

Goal # 0>t>pen.

Subj=pl, I.obj=team, score=s,

Order of goal

…

Event ID

Time Subcat/Modification Metadata

Off-line Task

Events indexed in video recording

1:0

60 m25 m25 m

SchollBasler

CampbellMatthäusBaslerNeville

DribblingFreekick

28min24 min18 min17 min

DefensePassGoalFoul

Radio Commenting3 Languages

Radio Commenting3 Languages

Radio Commenting3 Languages

Audio Commenting (TV, Radio)3 Languages

NewspaperText

NewspaperText

NewspaperText

NewspaperTexts

3 Languages

NewspaperText

NewspaperText

NewspaperText

Tickers etc.3 Languages

multilingual IE

=> event tables

Merging of Annotations

Event = goal Player = Basler

Dist. = 25 m Time = 18

Score = 1:0

Event = goal Type = Freekick Player = Basler Dist. = 25 m Time = 17

Score: leading

Event = goal Player= Basler Team = GermanyTime = 18 Score = 1:0 Finalscore = 1:0

Event = goal Type = Freekick

Player = Basler Team = GermanyTime = 18 Score = 1:0 Final score = 1:0 Distance = 25 m

The Role of IE in MUMIS

• Information Extraction (IE) is the task of identifying, collecting and normalizing relevant information for a specific application or user.

• The relevant information is typically represented in form of predefined “templates”, which are filled by means of Natural Language (NL) analysis (Template = Event Table in MUMIS)

• IE combines pattern matching mechanisms, (shallow) NLP and domain knowledge (terminology and ontology).

Extension of our IE system in MUMIS

• Multilingual and multisource IE. Incremental information building

• Cross-document co-reference resolution• Combine Metadata and event extraction =>

better organisation and dynamic updating of information (KM)

• Multiple presentation of results: Template, Event table, integration in MPEG-7 XML and Hyperlinks (Named Entities, rel. to Knowledge Management)

The DFKI Implementation

• Based on XML output of SPPC (Dev. At DFKI)

• Mapping the XML into a feature structure (the CorpA/schug Program)

• Cascaded grammar descriptions for enriching (or correcting) the SPPC output

• Including agreement processing and detection of grammatical functions

• Adapting the “Paradime triangle” for template generation and filling

Information Extraction

IE is generally subdivided in following tasks:- Named Entity task (NE) - Template Element task (TE)- Template Relation task (TR)- Scenario Template task (ST) - Co-reference task (CO)

Subtasks of IE

• Named Entity task (NE): Mark into the text each string that represents, a person, organization, or location name, or a date or time, or a currency or percentage figure.

• Template Element task (TE): Extract basic information related to organization, person, and artifact entities, drawing evidence from everywhere in the text.

Subtasks of IE (2)

• Template Relation task (TR): Extract relational information on employee_of, manufacture_of, location_of relations etc. (TR expresses domain-independent relationships).

• Scenario Template task (ST): Extract pre-specified event information and relate the event information to particular organization, person, or artifact entities (ST identifies domain and task specific entities and relations).

• Co-reference task (CO): Capture information on co-referring expressions, i.e. all mentions of a given entity, including those marked in NE and TE.

IE applied to soccer

Terms as descriptors for the NE task Team: Titelverteidiger Brasilien, den respektlosen

Außenseiter Schottland Player:Superstar Ronaldo, von Bewacher Calderwood noch

von Abwehrchef Hendry, von Jackson als drittem Stürmer, Torschütze Cesar, von Roberto Carlos (16.),

Referee: vom spanischen Schiedsrichter Garcia ArandaTrainer: Schottlands Trainer Brown, Kapitän Hendry seinen

Keeper LeightonLocation: im Stade de France von St. Denis (more fine-

grained location detection would be: Stadion: im Stade de France and City: von St. Denis )

Attendance: Vor 80000 Zuschauern

IE applied to soccer (2)

Terms for NE TaskTime: in der 73. Minute, nach gerade einmal 3:50 Minuten,

von Roberto Carlos (16.), nach einer knappen halben Stunde, scheiterte Rivaldo (49./52.) jeweils nur knapp, das vor der Pause Versäumte versuchten die Brasilianer nach Wiederbeginn, ...

Date: am Mittwoch, der Turnierstart (?), im WM-Eröffnungsspiel (?)

Score/Result: Brasilien besiegt Schottland 2:1, einen 2:1 (1:1)-Sieg, der zwischenzeitliche Ausgleich, in der 4. Minute in Führung gebracht, köpfte zum 1:0 ein

IE applied to soccer (3)

Relations for TR TaskOpponents: Brasilien besiegt Schottland, feierte der Top-

Favorit ... einen glücklichen 2:1 (1:1)-Sieg über den respektlosen Außenseiter Schottland,

Player_of: hatte Cesar Sampaio den vierfachen Weltmeister ... in Führung gebracht, Collins gelang ... der zwischenzeitliche Ausgleich für die Schotten, der Keeper des FC Aberdeen, Brasiliens Keeper Taffarel

Trainer_of: Schottlands Trainer Brown...

IE applied to soccer (4)

Events for ST task:Goal: in der 4. Minute in Führung gebracht, das schnellste

Tor ... markiert, Cesar Sampaio köpfte zum 1:0 ein, Collins (38.) verwandelte den Strafstoß, hätte Kapitän Hendry seinen Keeper Leighton um ein Haar zum zweiten Mal bezwungen, von dem der Ball ins Tor prallte

Foul: als er den durchlaufenden Gallacher im Strafraum allzu energisch am Trikot zog

Substitution: und mußte in der 59. Minute für Crespo Platz machen...

IE applied to soccer (5)

Description of the Templates: Teamteam-templateTACTIC [ ] SCORE [ ]NAME [ ]PLAYER [ ]TRAINER [ ]

goal-templateTIME [ ]SCORE [S]PLAYER [P]TEAM [team-templ ]TYPE [ ]SUCCESS [ ]

team-templateTACTIC [ ] SCORE [S]NAME [ ]PLAYER [P]TRAINER [ ]

Merging Component

• Acting on the generated formal annotations (Metadata and Events), but also interleaving with the generation process of those

• Checking consistency, eliminating redundancy (Template Merging), in accordance with domain ontology

• Completing the information with domain knowledge, inference Machine

Use of Standards

• XML as the annotation language and data interchange format

• MPEG-7: standard for the description of features of multimedia content, XML compliant (for content description), with a slot for textual annotations

More about MPEG (Moving Picture Coding Experts Group)

• MPEG-1: For the storage and retrieval of movie pictures and audio on storage media

• MPEG-2: For digital television• MPEG-4: Codes content as objects and

enables those objects to be manipulated

• MPEG-7: Where 1,2 and 4 make content available, MPEG-7 allows to find the content one needs

On-line Tasks

Searching and Displaying

• Search for interesting events with formal queriesGive me all goals from Overmars shot with his head in 1.

Half.Event=Goal; Player=Overmars; Time<=45; Previous-

Event=Headball

• Indicate hits by thumbnails & let user select scene

• Play scene via the Internet & allow scrollingOf course: slow motion, fast play, start/stop, etc

On-line Tasks

Searching and Displaying

• Search for interesting events with formal queriesGive me all goals from Overmars shot with his head in 1.

Half.Event=Goal; Player=Overmars; Time<=45; Previous-

Event=Headball

• Indicate hits by thumbnails & let user select scene

• Play scene via the Internet & allow scrollingOf course: slow motion, fast play, start/stop, etc

On-line Tasks

Knowledge GuidedUser Interface

&Search Engine

München - Ajax1998

München - Porto1996

Deutschland - Brasilien1998

PlayMovie

Fragmentof that Game

Freekick Goal Pass Defense

17 min 18 min 24 min 28min

Foul Freekick Dribbling

Kohler Basler Matthäus Wörns

Basler Bierhoff

25 m 25 m 60 m

On-line SW Architecture

ClientApplet

JMF

WWW ServerJava Server

MediaServer MPEG1

MediaServer MPEG1

MediaServer MPEG1

DBServer rDBMS

MediaServer MPEG1

FileServer

HTTPRMI

RMI (RTP, RTSP)

JDBC

Client Objects

Hit Rendering Objects

Media Server Objects

Query Engine Objects

MetadataAnnotations

KeyframesMPEG Movies

Lexica

Ontology

Query interface:• pre-selection• guided by domain knowledge• interactive, visual feedback

Server structure:• fully distributed• JMF media presentation • RMI-based interaction

On-line HW Architecture

• efficient & reliable storage management (near-line capacity, media change, 2. Location)

• high storage capacity (n TB, 1 h MPEG1 = 1 GB)• powerful media servers / powerful network

RAID

TapeLibrary

FC Switch

Media Server

Media Server

GB Switch

Internet

1GbpsGb-Switch

Router

Acknowledgements

• UEFA

• DFB, FA, KNVB

• EBU, WDR, NOS, SWR