The below is excerpted from an email I sent to some friends at an unnamed tech company, regarding my documentary This is Fi. I think this would actually work as a way to crowdsource documentary film logging and transcription – allowing people to donate labor instead of cash.

The Problem:

* We have over 100+ hours of footage (video diaries) of a man who speaks accented English.

* The first step in turning those 100+ hours into a 90-minute movie and a rich media website is transcribing and logging the footage.

* The cheapest cost I’ve found for this task is $50/hour of footage by an Indian offshoring company called REDACTED. This would mean a minimum of $5000 to get started on the movie.

* If we don’t hire it out, we’re looking at 400-600 man hours of doing the logging/transcription ourselves.

We were just granted non-profit sponsorship for our doc… Which means that my partner and I are about to go beat the bushes for $5K in donations just to transcribe the film. Ouch!

Buy what if we weren’t asking for cash? What if we could ask – even our brokest friends – for a donation of time and boredom.

Proposed Solution:

* What if we broke our hundred hours of footage into manageable sizes (15 seconds) and crowd-sourced the transcription. (Like Aaron Koblin’s work with Mechanical Turk.)

* The structure would be the video version of the recaptcha project – people’s transcription would be checked against other transcriptions… Sometimes a user would be providing a first pass, often they’d be validating.

* “Donations” of transcription would be charted against the goal (think “Kickstarter”). People would be able to see the impact they’d had on the process.

Why this matters:

* Distributed logging could be a significant cost-cutter not only for doc projects, but for corporate video/reality shows/etc. It’s a way to aggregate the time of interns/support staff/even audience members into meaningful work without wasting resources on managing volunteers.

* Metadata collected here could be an early part of the feedback loop – just by adding opinion information to the logging data… For example: what did you see? How compelling was it on a scale of 1 to 5?

* Even if not using volunteers – paying micropayments of 10 cents per 15 seconds would be a drastic reduction in cost over conventional logging. Paying by the second could bring a huge savings to production co’s IF there was some way to track the data from the original source footage, to the review area, and back.

The question:

* Is this possible?

* What are the stumbling blocks of breaking-down and reconstituting the footage and associated metadata? Can editing software talk to the net?

* Do you know of a solution that does this already? This is probably ridiculous – but could you batch-upload to YouTube and then scrape YouTube comments for logging info?

What do YOU think? None of us have money to donate to a film… What about time? A little effort? What if it was a game? Would you compete against friends? Would this be more/less boring than minesweeper/solitaire?

First-person documentary is a bit of an obsession of mine. I’m making a documentary on my friend, Fi, and 90% of the footage is stuff he shot. His self-filmed DV is far more interesting, raw, and compelling than our “professionally filmed” HD.

The challenge to this methodology is editorially – how do you filter hundreds of hours of video diaries? How do you sculpt a journal into a narrative?

This problem is the same problem that keeps people from cutting home movies into anything self-contained. Editorial is time-consuming, tedious and requires a custom skill set. But, what if you could take the judgments that are behind editorial decisions and automate them? What if you could use thumbs-up/thumbs-down voting and/or tagging to allow people to shape an edit? What if you used social networking behavior to allow an automated edit to know that John is more interested in footage pertaining to his friend Sam and his girlfriend Kate than he is in his acquaintance Mike?

I proposed a system of mobile devices that recognize proximity, social relationships and shoot high-quality video. Picture this: you go to a party with a bunch of friends. All of you film with your smart, high-quality cameraphones. At night, while you sleep, the phones upload footage and create an assembly based on the order in which things happened and physical proximity (i.e. the phone knows if two people were filming the same conversation, dance, striptease, etc). When you wake up in the morning, you watch a video. You click a thumbs up for shots you like, a thumbs down for shots you don’t, and you tag people you recognize. When your friend watches the video 2 hours later, the choices you made about the video have further refined the edit. He, too, makes decisions. Each re-viewing of the video produces a more finished version.

If you and your friends did this all the time, you’d end up with an on-going series about your lives – particularly the events when cameras are most present: concerts, parties, weddings, graduations, sports events, road trips, etc.

I worked with my friends Tony and Sooyoung at Favorite Medium on this deck. Nokia didn’t go for it, but I still believe in the idea. Someone should do this. If you think it’s a good idea, call me.

A PDF is here.