CAT | Interesting Technology
Software that recognizes mood is apparently used in call centers – could be used to derive metadata for pre-post logging (and story derivation). Imagine a keyword collection for “happy” or “stressed” or whatever mood happens to be demonstrate in the audio content. I’m not sure if the technologies are related but Affectiva have demonstrated emotion-detecting software in the past.
With speech-to-text, keyword extraction, mood extraction the basic logging of reality and documentary could be done in pre-post and handed to the editor.
After Terry Curren’s round up of last year’s Hollywood Post Alliance Retreat I decided I should attend this year. While I was working on marketing for Lumberjack – our real time location logging tool – I got an email from the HPA offering spaces in the demo room during the retreat. It was immediately obvious that this was the time and place to reveal what we’ve been working for the last 8-9 months.
I have a strong interest – personally and professionally – to want to automate the boring parts of post-production away from humans to computers, extending to some of the basic string-outs. This seems to infringe on the “human” role in postproduction, at least according to some of my associates. Well, lately I’ve come across a whole range of stories on how traditionally human roles, like doctors (and assistant editors), can or will be automated out of existence. That’s led me to think about what is the essential role of the human that can’t be automated? It’s not a simple question. (more…)
Pixels – those little dots that make up all our video images – are hard to encode and push down pipelines, even with ever-increasing encoding efficiency. On the other hand, vectors are small and very efficient, but so far have proved difficult to apply to video content. (more…)
As I’m sure you’re all aware, my special interest is in the Pre-post production area, specifically how we can automate out the boring work and optimize workflow for editors to do their thing in turning the raw material into a polished gem.
Of course, metadata is going to play a big part in doing this. In fact, story building algorithms are relatively easy – as we demonstrate with First Cuts Studio. What is hard is to derive the necessary metadata without taking the time for a human to enter it.
If we ever want to be able to judge performance or recognize emotion in a face in a shot, we need a computer to recognize emotion. And they are. In the New York Times from October 15th comes But How Do You Really Feel? Someday the Computer May Know: (more…)
Traditionally movies got greenlit on the “gut feeling” of some executive. After failures like John Carter from Mars perhaps it’s time to consider some modern, data-intensive methods instead. (I love big data and what it can tell us.) (more…)
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…)