CAT | Interesting Technology
Expect Labs’ MindMeld iPad App Understands Your Conversations In Real Time http://t.co/Y8Mx9PWC
First off, I need this! (more…)
FBI launches $1 billion face recognition project http://t.co/G7SSZclO
The technology behind facial recognition is growing better all the time. Various companies, including Apple, are building up portfolios of relevant technology to implement into their application. Now the FBI have their own “application” (catching bad guys) but: (more…)
Yes, the lack of need for a browser plug-in is good, but that’s the role of HTML5 which has largely standardized on H.264/MP4 (thank goodness). It will be hard to win against the momentum behind HTML5 and frankly I’d prefer there not to be another alternative, now that we have finally got something like a standard.
Personally, I think this is an interesting technology looking for a reason to exist. I find the claims of “90% less bandwidth” to be suspect at best, and the company provides no details on their site (that I could find).
Australian news website ITwire, has an article up about the MPEG’s announcement of the draft standard of their next generation of video codec, due to replace H.264 over time. Hopefully now that we’ve mostly settled on H.264 as the “one codec to rule them all” it will be a comfortable transition to the next generation. (more…)
Last night we arrived back from the Solar Odyssey as our involvement finished on Sunday (long story shot, “creative differences”) and today my welcome home present to myself – a nice new MacBook Pro retina. Naturally I immediately updated to Mountain Lion. (New machine, new OS, might as well get it all over together).
One of the first apps I was looking at was Final Cut Pro X – very nice to see a full size 1080P signal in the Viewer window 1:1 and still have a whole heap of screen real estate. (My confession is that I’m using all the pixels 1:1 not in Retina mode. I already have to wear glasses for a computer screen so I might as well capitalize on it.)
Of course I look through the menus and what do I find in the Edit menu but: (more…)
Kaggle’s algorithms show machines are getting too good at judging humans http://t.co/sltVPexI
Regular readers will know I’m fascinated by research and technology that has computers understanding human behavior. My interest is personal, but also professionally I’m interested in how these technologies can be adapted to take some of the more boring work out of some types of production.
The article presents two more data points. I’ll just post the summaries.
An algorithm is no less reliable at scoring essays than the average teacher.
With only 140 characters, data scientists and statisticians can get a strong sense for your personality. That’s fairly worrying, considering that this information could get into the wrong hands.
Make of it what you will.
Seamless Video Editing – A Look Toward the Future http://t.co/ILZFqHDd
A provocative first paragraph:
A new application being developed by researchers at UC Berkely and Adobe Systems aims to do just that…helping editors identify the best spot to make a cut based off of audio and visual features of raw footage. The program can auto generate seamless transitions to make the cuts visually smooth and undetectable.
Which sounds exciting, until you read later:
This tech seems useful for working with on-camera interviews (with only one subject), but in it’s current state it doesn’t seem like it would be effective at tackling more complex shooting situations.
So, which is it? Both and neither. Understanding how and why we make edits is complex, but it is/will be doable. Finding the base information on which to apply that algorithm is even harder. But it is inevitable. Certainly not for every type of edit, and not for every project. Given that an enormous amount of editing is not highly “creative” but somewhat routine.
I have long advocated that this type of technology will be developed and applied. When we were developing First Cuts, the algorithm would product a result and it would be “off” in some way – simply not what I would have done as an editor. That forced an examination of how I would have made the edit. That then lead to needing to quantify why I made the edit there.
That part was not easy, although I am fortunate to have a brain almost equally balanced between left and right – creative and analytic.
In layman’s terms: Spots of the video where there is little audio or on-screen movement are given priority as ideal spots to cut, and are plotted on a “cut suitability” timeline. If necessary the application will insert natural looking pauses to bridge two cuts together. From the product demo (embedded below) it appears that editors can simply delete text from the transcript view and the application will go to work creating a seamless transition. An additional features allows for one-click removal of “ums” and repeated words.
They can go back one step. In an interview situation you generally have two voices: breaking an interview up on voice changes, and then paragraph breaks (which is what this research seems to be doing, but adding in the analysis of motion in video) is “trivial” once we get reliable speech transcription.
Reliable speech transcription is the key to unlocking an enormous amount of metadata-driven tagging/keywording and driving these sorts of automatic assembles. At this stage I see this more as an editor’s tool than for finished projects, although there are some applications in exploring large amounts of video material. (Something I hope to demonstrate by the end of the year using some of the Solar Odyssey footage.)
Should we go down this path? That’s an irrelevant question because, with downward budget pressures dominant in the industry, it’s inevitable. Those that can work smarter – using all the tools at their disposal – will continue to be needed.
And I firmly believe that the emotionally compelling, heart-tugging edit is going to remain beyond the ability of a computer for the balance of my lifetime.