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The Family Video Archive: Organizing Memories

The Family Video Archive (FVA) is a system that helps you organize and annotate your home videos, making it easier to browse and search for specific moments. By combining manual and automated annotation techniques, FVA allows you to add relevant metadata to your videos, creating a valuable collection of memories.

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The Family Video Archive: Organizing Memories

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  1. The Family Video Archive:Organizing Memories or What I did on my summer vacation Gregory D. Abowd Assoc. Professor College of Computing and GVU Center

  2. Acknowledgments • Andreas Lachenmann & Matthias Gauger (U. Stuttgart, Germany) • FVA Demo is their work • Rudinei Goularte (USP-Brazil) & Niels van Hese (U. Delft, Netherlands) • Earlier prototypes of FVA • Molly Stevens (GT IDT program) • Worked on related Living Memory Box • Shwetak Patel (PhD program) • He’s in charge now

  3. Dedication • Richard G. Abowd, Jr. • My father, 1924-1998. • Founder of RGA Action Films. • His 8mm film collection is the original inspiration for this work.

  4. Outline • Motivation for FVA • Demo of FVA • Annotation/tagging • Search/browse • Issues in the design • General challenges and the future

  5. Motivation • Lots of video/movies • Some families have it now • It’s only getting easier to accumulate • Organization is hard • Worse than photographs • Makes it hard to enjoy viewing later on • If it were easier to browse videos… • Would our collections be more valuable? • Could you simplify the organization?

  6. Related Work • Digital Photography • PhotoMesa (Bedersen, 2001), PhotoFinder (Shneiderman), MSR (Platt et al.) • Manual/automated annotation, visualization and automated clustering • Digital video • Plenty of work on improving nonlinear editing (e.g., Hitchcock system from FX-PAL) • Vision community works on scene detection, object detection (e.g., MPEG-4) • Annotation schemes (MPEG-7, Dublin CORE) • Browsing/searching (Informedia at CMU) • Commercial systems (e.g., VideoLogger from Virage)

  7. What is our niche? • Family video • not professional quality • no closed caption information, so relatively no metadata • Not editing • getting right content • would feed an editing system • Interaction techniques that ride the balance between manual (tedious but rich and accurate) and automated (fast but error-prone) annotation. • Motivate better annotation at point of capture.

  8. Goal • Create a system to annotate home movies with relevant metadata to facilitate browsing and searching. • Effective symbiosis between manual and automated techniques. • Control/accuracy trade-off with speed

  9. The FVA prototype • Test case: RGA Action Films • 8mm film of Abowd family • 1955-1984 (then we switched to video) • Digitized into AVI format • Windows Media 9 codec • ~25 hours, ~17GBytes • BIG family • 12 siblings, 52 first cousins, 32 nieces/nephews) • I am currently adding my own family video from 1997-present

  10. FVA Demo • There is MUCH more functionality than we will show here. • See http://swiki.cc.gatech.edu:8080/ahome/97 for more details, including full Java/JMF source, installation instructions and very thorough user manual. • Paper in MIR 2003 available

  11. FVA Basics • Video archive is collection of video files • Broken up into arbitrary 5-minute chunks • Absolutely no other information, but I do have my father’s notes • User wants to divide files into scenes and associate meaning to scenes.

  12. Tagging scenes descriptions • Hierarchy of tags • Who • Where • Event • other major categories • Completely user-defined

  13. Scene metadata Albums Existing tagsuggestions Video window New tagsuggestions Video files Tag hierarchy scene boundary FVA: Annotation/Tagging

  14. Detailed Operation • How to annotate a scene • Free text (important from experience) • Date (flexible accuracy and quick) • Drag & drop tags • Automated suggestions of existing and new tags • Select “important” tags • Tag extent in scene (defaults to whole scene)

  15. Creating Scenes • One of the more arduous tasks. • Automated scene detection based on frame differencing. • Manually adjusted threshold. • Ultimately, this task goes away (e.g., iMovie) Threshold adjustment

  16. Zoomable scene browser Tags Querywindow Zoomable timeline filter FVA: Searching/browsing

  17. Detailed Operation • Zooming as filtering • Built using piccolo ZUI toolkit from Maryland • Semantic zooming based on tag hierarchy • Filter history visualized • Chaining filters • Timeline filtering • Video thumbnails • Album creation

  18. Design Issues • “Expert” interface • Daunting to beginner • Interface doesn’t suggest “right” way to use it (e.g. tag hierarchy, searching) • Acquiring video is still difficult

  19. Tagging • Tag hierarchy completely user defined • This idea is increasingly powerful. • There can be LOTS of them, so how to manage? • Dynamically drives the search interface. • Aliases provide further functionality (demo). • Parameterized tags (e.g. “John’s birthday). • Valid begin/end dates. • Tagging is made much easier, but it is still daunting and time-consuming. • Will anyone besides me ever do this? • You are never really done, but where is line of diminishing returns? • Symbiosis of manual/automated tasks

  20. Reflection and Future • We built it, so what? • I always wanted this. My family loves it! • Basically, I am happy regardless of what comes next (there is a lesson there). • There are research opportunities

  21. Future Work • Front-end • Link to an automated capture system, with stationary and mobile “feeds” • Tagging at point of capture (Who, Where, When, Event) • Back-end • Working with albums to feed nonlinear editing • Huge time saving for gathering content • Facilitating collaboration • Expert/novice interfaces and transitioning between • Alternatives to semantic zooming • Handling more dense archives • Are there more serious applications?

  22. Potential Uses • Analyzing individual development • Early diagnosis of disorders (e.g., autism) • Tracking intervention therapies • Shared, historically significant archives • HCI video collection • eClass-like lecture archives • Finding Lost Objects service

  23. Authoring Applications • Previous examples are all different enough from FVA • Adapting FVA not the right approach • Authoring environment to build FVA-like applications

  24. Questions?

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