SlideShare ist ein Scribd-Unternehmen logo
1 von 11
Downloaden Sie, um offline zu lesen
Creating a Synthetic Video Dataset for the VAST 2009 Challenge Mark A. Whiting, Carrie Varley, Jereme Haack Presented by Jean Scholtz BELIV 2010 03-28-2010
IEEE Visual Analytics Science and Technology (VAST) Annual Challenge – if you don’t know about it, you should review it ,[object Object],[object Object],[object Object],[object Object]
VAST 2009 Features the First Video Challenge ,[object Object],[object Object],[object Object],[object Object]
Was this a “synthetic” video?  ,[object Object],[object Object]
What was the scenario?  ,[object Object],[object Object]
What webcam did we pick?  ,[object Object]
Analysis Issues ,[object Object],[object Object]
What did we plant?  A scene where the Embassy employee “dupe” was meeting the handler outside the coffee shop and handing off information A scene where the handler was meeting another member of her criminal organization.  They did the old briefcase “switcheroo”.  See the light and dark cases.
How did we coordinate all the activities?  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Contestant Results: one example University of Stuttgart – using video perpetuograms to track people from between scenes and views to enhance continuity
Lessons Learned & Next Steps ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Weitere ähnliche Inhalte

Andere mochten auch

A Descriptive Model of Visual Scanning.
A Descriptive Model of Visual Scanning.A Descriptive Model of Visual Scanning.
A Descriptive Model of Visual Scanning.BELIV Workshop
 
Visualization Evaluation of the Masses, by the Masses, and for the Masses.
Visualization Evaluation of the Masses, by the Masses, and for the Masses.Visualization Evaluation of the Masses, by the Masses, and for the Masses.
Visualization Evaluation of the Masses, by the Masses, and for the Masses.BELIV Workshop
 
Pragmatic Challenges in the Evaluation of Interactive Visualization Systems.
Pragmatic Challenges in the Evaluation of Interactive Visualization Systems.Pragmatic Challenges in the Evaluation of Interactive Visualization Systems.
Pragmatic Challenges in the Evaluation of Interactive Visualization Systems.BELIV Workshop
 
Evaluating Information Visualization in Large Companies: Challenges, Experien...
Evaluating Information Visualization in Large Companies: Challenges, Experien...Evaluating Information Visualization in Large Companies: Challenges, Experien...
Evaluating Information Visualization in Large Companies: Challenges, Experien...BELIV Workshop
 
Beyond system logging: human logging for evaluating information visualization.
Beyond system logging: human logging for evaluating information visualization.Beyond system logging: human logging for evaluating information visualization.
Beyond system logging: human logging for evaluating information visualization.BELIV Workshop
 
Comparative Evaluation of Two Interface Tools in Performing Visual Analytics ...
Comparative Evaluation of Two Interface Tools in Performing Visual Analytics ...Comparative Evaluation of Two Interface Tools in Performing Visual Analytics ...
Comparative Evaluation of Two Interface Tools in Performing Visual Analytics ...BELIV Workshop
 
Focus Groups for Functional InfoVis Prototype Evaluation: A Case Study.
Focus Groups for Functional InfoVis Prototype Evaluation: A Case Study.Focus Groups for Functional InfoVis Prototype Evaluation: A Case Study.
Focus Groups for Functional InfoVis Prototype Evaluation: A Case Study.BELIV Workshop
 

Andere mochten auch (7)

A Descriptive Model of Visual Scanning.
A Descriptive Model of Visual Scanning.A Descriptive Model of Visual Scanning.
A Descriptive Model of Visual Scanning.
 
Visualization Evaluation of the Masses, by the Masses, and for the Masses.
Visualization Evaluation of the Masses, by the Masses, and for the Masses.Visualization Evaluation of the Masses, by the Masses, and for the Masses.
Visualization Evaluation of the Masses, by the Masses, and for the Masses.
 
Pragmatic Challenges in the Evaluation of Interactive Visualization Systems.
Pragmatic Challenges in the Evaluation of Interactive Visualization Systems.Pragmatic Challenges in the Evaluation of Interactive Visualization Systems.
Pragmatic Challenges in the Evaluation of Interactive Visualization Systems.
 
Evaluating Information Visualization in Large Companies: Challenges, Experien...
Evaluating Information Visualization in Large Companies: Challenges, Experien...Evaluating Information Visualization in Large Companies: Challenges, Experien...
Evaluating Information Visualization in Large Companies: Challenges, Experien...
 
Beyond system logging: human logging for evaluating information visualization.
Beyond system logging: human logging for evaluating information visualization.Beyond system logging: human logging for evaluating information visualization.
Beyond system logging: human logging for evaluating information visualization.
 
Comparative Evaluation of Two Interface Tools in Performing Visual Analytics ...
Comparative Evaluation of Two Interface Tools in Performing Visual Analytics ...Comparative Evaluation of Two Interface Tools in Performing Visual Analytics ...
Comparative Evaluation of Two Interface Tools in Performing Visual Analytics ...
 
Focus Groups for Functional InfoVis Prototype Evaluation: A Case Study.
Focus Groups for Functional InfoVis Prototype Evaluation: A Case Study.Focus Groups for Functional InfoVis Prototype Evaluation: A Case Study.
Focus Groups for Functional InfoVis Prototype Evaluation: A Case Study.
 

Ähnlich wie Generating a synthetic video dataset

A Neural Network Approach to Deep-Fake Video Detection
A Neural Network Approach to Deep-Fake Video DetectionA Neural Network Approach to Deep-Fake Video Detection
A Neural Network Approach to Deep-Fake Video DetectionIRJET Journal
 
Video & AI: capabilities and limitations of AI in detecting video manipulations
Video & AI: capabilities and limitations of AI in detecting video manipulationsVideo & AI: capabilities and limitations of AI in detecting video manipulations
Video & AI: capabilities and limitations of AI in detecting video manipulationsVasileiosMezaris
 
IRJET- A Review on Moving Object Detection in Video Forensics
IRJET- A Review on Moving Object Detection in Video Forensics IRJET- A Review on Moving Object Detection in Video Forensics
IRJET- A Review on Moving Object Detection in Video Forensics IRJET Journal
 
Automatic video censoring system using deep learning
Automatic video censoring system using deep learningAutomatic video censoring system using deep learning
Automatic video censoring system using deep learningIJECEIAES
 
IRJET - Using Convolutional Neural Network in Surveillance Videos for Recogni...
IRJET - Using Convolutional Neural Network in Surveillance Videos for Recogni...IRJET - Using Convolutional Neural Network in Surveillance Videos for Recogni...
IRJET - Using Convolutional Neural Network in Surveillance Videos for Recogni...IRJET Journal
 
MINI PROJECT 2023 deepfake detection.pptx
MINI PROJECT 2023 deepfake detection.pptxMINI PROJECT 2023 deepfake detection.pptx
MINI PROJECT 2023 deepfake detection.pptxswathiravishankar3
 
Videos about static code analysis
Videos about static code analysisVideos about static code analysis
Videos about static code analysisPVS-Studio
 
IRJET - Deepfake Video Detection using Image Processing and Hashing Tools
IRJET - Deepfake Video Detection using Image Processing and Hashing ToolsIRJET - Deepfake Video Detection using Image Processing and Hashing Tools
IRJET - Deepfake Video Detection using Image Processing and Hashing ToolsIRJET Journal
 
A Thorough Study on Video Integrity using Blockchain
A Thorough Study on Video Integrity using BlockchainA Thorough Study on Video Integrity using Blockchain
A Thorough Study on Video Integrity using Blockchainijtsrd
 
Mere Paas Teensy Hai (Nikhil Mittal)
Mere Paas Teensy Hai (Nikhil Mittal)Mere Paas Teensy Hai (Nikhil Mittal)
Mere Paas Teensy Hai (Nikhil Mittal)ClubHack
 
Chaos Engineering Without Observability ... Is Just Chaos
Chaos Engineering Without Observability ... Is Just ChaosChaos Engineering Without Observability ... Is Just Chaos
Chaos Engineering Without Observability ... Is Just ChaosCharity Majors
 
DEEPFAKE DETECTION TECHNIQUES: A REVIEW
DEEPFAKE DETECTION TECHNIQUES: A REVIEWDEEPFAKE DETECTION TECHNIQUES: A REVIEW
DEEPFAKE DETECTION TECHNIQUES: A REVIEWvivatechijri
 
The human side of multimedia systems
The human side of multimedia systemsThe human side of multimedia systems
The human side of multimedia systemsMichael Riegler
 
Panacea - Augmented Reality
Panacea - Augmented Reality Panacea - Augmented Reality
Panacea - Augmented Reality Ritesh Nayak
 
VOGIN-IP-lezing-Zeno_ geradts
VOGIN-IP-lezing-Zeno_ geradtsVOGIN-IP-lezing-Zeno_ geradts
VOGIN-IP-lezing-Zeno_ geradtsvoginip
 
Exploiting The Social Aspects Of Web 2.0 In HE Institutions
Exploiting The Social Aspects Of Web 2.0 In HE InstitutionsExploiting The Social Aspects Of Web 2.0 In HE Institutions
Exploiting The Social Aspects Of Web 2.0 In HE Institutionslisbk
 
Huawei STW 2018 public
Huawei STW 2018 publicHuawei STW 2018 public
Huawei STW 2018 publicAlan Smeaton
 

Ähnlich wie Generating a synthetic video dataset (20)

A Neural Network Approach to Deep-Fake Video Detection
A Neural Network Approach to Deep-Fake Video DetectionA Neural Network Approach to Deep-Fake Video Detection
A Neural Network Approach to Deep-Fake Video Detection
 
Video & AI: capabilities and limitations of AI in detecting video manipulations
Video & AI: capabilities and limitations of AI in detecting video manipulationsVideo & AI: capabilities and limitations of AI in detecting video manipulations
Video & AI: capabilities and limitations of AI in detecting video manipulations
 
IRJET- A Review on Moving Object Detection in Video Forensics
IRJET- A Review on Moving Object Detection in Video Forensics IRJET- A Review on Moving Object Detection in Video Forensics
IRJET- A Review on Moving Object Detection in Video Forensics
 
Automatic video censoring system using deep learning
Automatic video censoring system using deep learningAutomatic video censoring system using deep learning
Automatic video censoring system using deep learning
 
IRJET - Using Convolutional Neural Network in Surveillance Videos for Recogni...
IRJET - Using Convolutional Neural Network in Surveillance Videos for Recogni...IRJET - Using Convolutional Neural Network in Surveillance Videos for Recogni...
IRJET - Using Convolutional Neural Network in Surveillance Videos for Recogni...
 
MINI PROJECT 2023 deepfake detection.pptx
MINI PROJECT 2023 deepfake detection.pptxMINI PROJECT 2023 deepfake detection.pptx
MINI PROJECT 2023 deepfake detection.pptx
 
Videos about static code analysis
Videos about static code analysisVideos about static code analysis
Videos about static code analysis
 
IRJET - Deepfake Video Detection using Image Processing and Hashing Tools
IRJET - Deepfake Video Detection using Image Processing and Hashing ToolsIRJET - Deepfake Video Detection using Image Processing and Hashing Tools
IRJET - Deepfake Video Detection using Image Processing and Hashing Tools
 
A Thorough Study on Video Integrity using Blockchain
A Thorough Study on Video Integrity using BlockchainA Thorough Study on Video Integrity using Blockchain
A Thorough Study on Video Integrity using Blockchain
 
Mere Paas Teensy Hai (Nikhil Mittal)
Mere Paas Teensy Hai (Nikhil Mittal)Mere Paas Teensy Hai (Nikhil Mittal)
Mere Paas Teensy Hai (Nikhil Mittal)
 
Chaos Engineering Without Observability ... Is Just Chaos
Chaos Engineering Without Observability ... Is Just ChaosChaos Engineering Without Observability ... Is Just Chaos
Chaos Engineering Without Observability ... Is Just Chaos
 
Mike Doane: Mike Doane
Mike Doane: Mike DoaneMike Doane: Mike Doane
Mike Doane: Mike Doane
 
DEEPFAKE DETECTION TECHNIQUES: A REVIEW
DEEPFAKE DETECTION TECHNIQUES: A REVIEWDEEPFAKE DETECTION TECHNIQUES: A REVIEW
DEEPFAKE DETECTION TECHNIQUES: A REVIEW
 
The human side of multimedia systems
The human side of multimedia systemsThe human side of multimedia systems
The human side of multimedia systems
 
Panacea - Augmented Reality
Panacea - Augmented Reality Panacea - Augmented Reality
Panacea - Augmented Reality
 
VOGIN-IP-lezing-Zeno_ geradts
VOGIN-IP-lezing-Zeno_ geradtsVOGIN-IP-lezing-Zeno_ geradts
VOGIN-IP-lezing-Zeno_ geradts
 
Butler
ButlerButler
Butler
 
Exploiting The Social Aspects Of Web 2.0 In HE Institutions
Exploiting The Social Aspects Of Web 2.0 In HE InstitutionsExploiting The Social Aspects Of Web 2.0 In HE Institutions
Exploiting The Social Aspects Of Web 2.0 In HE Institutions
 
Huawei STW 2018 public
Huawei STW 2018 publicHuawei STW 2018 public
Huawei STW 2018 public
 
Fake News Analyzer
Fake News AnalyzerFake News Analyzer
Fake News Analyzer
 

Mehr von BELIV Workshop

Look Before You Link: Eye Tracking in Multiple Coordinated View Visualization.
Look Before You Link: Eye Tracking in Multiple Coordinated View Visualization.Look Before You Link: Eye Tracking in Multiple Coordinated View Visualization.
Look Before You Link: Eye Tracking in Multiple Coordinated View Visualization.BELIV Workshop
 
Many Roads Lead to Rome. Mapping Users’ Problem Solving Strategies.
Many Roads Lead to Rome. Mapping Users’ Problem Solving Strategies.Many Roads Lead to Rome. Mapping Users’ Problem Solving Strategies.
Many Roads Lead to Rome. Mapping Users’ Problem Solving Strategies.BELIV Workshop
 
Proposed Working Memory Measures for Evaluating Information Visualization Tools.
Proposed Working Memory Measures for Evaluating Information Visualization Tools.Proposed Working Memory Measures for Evaluating Information Visualization Tools.
Proposed Working Memory Measures for Evaluating Information Visualization Tools.BELIV Workshop
 
How is a graphic like pumpkin pie? A framework for analysis and critique of v...
How is a graphic like pumpkin pie? A framework for analysis and critique of v...How is a graphic like pumpkin pie? A framework for analysis and critique of v...
How is a graphic like pumpkin pie? A framework for analysis and critique of v...BELIV Workshop
 
Implications of Individual Differences on Evaluating Information Visualizatio...
Implications of Individual Differences on Evaluating Information Visualizatio...Implications of Individual Differences on Evaluating Information Visualizatio...
Implications of Individual Differences on Evaluating Information Visualizatio...BELIV Workshop
 
Is Your User Hunting or Gathering Insights? Identifying Insight Drivers Acros...
Is Your User Hunting or Gathering Insights? Identifying Insight Drivers Acros...Is Your User Hunting or Gathering Insights? Identifying Insight Drivers Acros...
Is Your User Hunting or Gathering Insights? Identifying Insight Drivers Acros...BELIV Workshop
 
Scanning Between Graph Visualizations: An Eye Tracking Evaluation.
Scanning Between Graph Visualizations: An Eye Tracking Evaluation.Scanning Between Graph Visualizations: An Eye Tracking Evaluation.
Scanning Between Graph Visualizations: An Eye Tracking Evaluation.BELIV Workshop
 
Learning-Based Evaluation of Visual Analytic Systems.
Learning-Based Evaluation of Visual Analytic Systems.Learning-Based Evaluation of Visual Analytic Systems.
Learning-Based Evaluation of Visual Analytic Systems.BELIV Workshop
 
BELIV'10 Keynote: Conceptual and Practical Challenges in InfoViz Evaluations
BELIV'10 Keynote: Conceptual and Practical Challenges in InfoViz EvaluationsBELIV'10 Keynote: Conceptual and Practical Challenges in InfoViz Evaluations
BELIV'10 Keynote: Conceptual and Practical Challenges in InfoViz EvaluationsBELIV Workshop
 

Mehr von BELIV Workshop (9)

Look Before You Link: Eye Tracking in Multiple Coordinated View Visualization.
Look Before You Link: Eye Tracking in Multiple Coordinated View Visualization.Look Before You Link: Eye Tracking in Multiple Coordinated View Visualization.
Look Before You Link: Eye Tracking in Multiple Coordinated View Visualization.
 
Many Roads Lead to Rome. Mapping Users’ Problem Solving Strategies.
Many Roads Lead to Rome. Mapping Users’ Problem Solving Strategies.Many Roads Lead to Rome. Mapping Users’ Problem Solving Strategies.
Many Roads Lead to Rome. Mapping Users’ Problem Solving Strategies.
 
Proposed Working Memory Measures for Evaluating Information Visualization Tools.
Proposed Working Memory Measures for Evaluating Information Visualization Tools.Proposed Working Memory Measures for Evaluating Information Visualization Tools.
Proposed Working Memory Measures for Evaluating Information Visualization Tools.
 
How is a graphic like pumpkin pie? A framework for analysis and critique of v...
How is a graphic like pumpkin pie? A framework for analysis and critique of v...How is a graphic like pumpkin pie? A framework for analysis and critique of v...
How is a graphic like pumpkin pie? A framework for analysis and critique of v...
 
Implications of Individual Differences on Evaluating Information Visualizatio...
Implications of Individual Differences on Evaluating Information Visualizatio...Implications of Individual Differences on Evaluating Information Visualizatio...
Implications of Individual Differences on Evaluating Information Visualizatio...
 
Is Your User Hunting or Gathering Insights? Identifying Insight Drivers Acros...
Is Your User Hunting or Gathering Insights? Identifying Insight Drivers Acros...Is Your User Hunting or Gathering Insights? Identifying Insight Drivers Acros...
Is Your User Hunting or Gathering Insights? Identifying Insight Drivers Acros...
 
Scanning Between Graph Visualizations: An Eye Tracking Evaluation.
Scanning Between Graph Visualizations: An Eye Tracking Evaluation.Scanning Between Graph Visualizations: An Eye Tracking Evaluation.
Scanning Between Graph Visualizations: An Eye Tracking Evaluation.
 
Learning-Based Evaluation of Visual Analytic Systems.
Learning-Based Evaluation of Visual Analytic Systems.Learning-Based Evaluation of Visual Analytic Systems.
Learning-Based Evaluation of Visual Analytic Systems.
 
BELIV'10 Keynote: Conceptual and Practical Challenges in InfoViz Evaluations
BELIV'10 Keynote: Conceptual and Practical Challenges in InfoViz EvaluationsBELIV'10 Keynote: Conceptual and Practical Challenges in InfoViz Evaluations
BELIV'10 Keynote: Conceptual and Practical Challenges in InfoViz Evaluations
 

Generating a synthetic video dataset

  • 1. Creating a Synthetic Video Dataset for the VAST 2009 Challenge Mark A. Whiting, Carrie Varley, Jereme Haack Presented by Jean Scholtz BELIV 2010 03-28-2010
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8. What did we plant? A scene where the Embassy employee “dupe” was meeting the handler outside the coffee shop and handing off information A scene where the handler was meeting another member of her criminal organization. They did the old briefcase “switcheroo”. See the light and dark cases.
  • 9.
  • 10. Contestant Results: one example University of Stuttgart – using video perpetuograms to track people from between scenes and views to enhance continuity
  • 11.