[v2 dev] Milestone 2 - Frame Detection

#1

Summary
A series of tests to determine the best method for detecting and triggering the capture of a frame. The results should reveal a design that is most likely to give consistent results given a variety of film stocks.

The most important mechanism in Kinograph is determining when to take a photograph . There is more than one way to determine when the right time is. We could use the film’s perforations, or we could use a camera to detect when a new frame is ready to be photographed. This phase will test those two different approaches to see which is more effective.

Required

  • Variety of film stocks in 35mm and 16mm with varying levels of perf damage
  • trip to NYC to install camera system with BKR
  • purchase of computer system for controlling camera and its software
  • new gate design

Deliverables:

  • Design specifications for a frame detection system.
  • Weekly updates from BKR to be shared with community
#2

Hey all, a quick video here describing a possible approach to frame detection. Please let me know what you think!

One thing I forgot to say in the video, the value of L should be updated after each successful frame extraction so that it is the average of all the L2 adjustments made in the sequence so far. Something like N(L + L2)/N

Also, I’m searching for 35mm and 16mm reels we can test with. If you have film we can use (and not give back to you) please contact me: info@kinograph.cc.

#3

Also putting this here as a new option. Thanks to Martín Piñeyro for sending me this. His blog can be found here: http://www.blog.mpineyro.com/

https://vimeo.com/212660744

#4

openCV has quite a few algorithms (optical flow/tracker) which might be able to estimate the shifts you are describing in your video. Some are also reasonably fast.

So one could just do the capture with a mostly free running camera, store the resulting images on disk and align them (calculate your “L”) in a later processing step.

One needs a sufficiently larger overlap between neighbouring captures, slightly more disk space (because of the overlap required between frames) and some additional processing time (from my experience, anything between 300 msec and 1 sec per frame).