Extracting Lightning Strikes From HD Video

Lightning photography is a fine art. It requires a lot of patience, and until recently required some fancy gear. [Saulius Lukse] has always been fascinated by lightning storms. When he was a kid he used to shoot lightning with his dad’s old Zenit camera — It was rather challenging. Now he’s figured out a way to do it using a GoPro.

He films at 1080@60, which we admit, isn’t the greatest resolution, but we’re sure the next GoPro will be filming 4K60 next. This means you can just set up your GoPro outside during the storm, and let it do it what it does best — film video. Normally, you’d then have to edit the footage and extract each lightning frame. That could be a lot of work.

[Saulius] wrote a Python script using OpenCV instead. Basically, the OpenCV script spots the lightning and saves motion data to a CSV file by detecting fast changes in the image.

graph of lightning

The result? All the lightning frames plucked out from the footage — and it only took an i7 processor about 8 minutes to analyze 15 minutes of HD footage. Not bad.

Now if you feel like this is still cheating, you could build a fancy automatic trigger for your DSLR instead…

Hyperlapse Makes Your HeadCam Videos Awesome

hyperlapse First person video – between Google Glass, GoPro, and other sports cameras, it seems like everyone has a camera on their head these days. If you’re a surfer or skydiver, that might make for some awesome footage. For the rest of us though, it means hours of boring video. The obvious way to fix this is time-lapse. Typically time-lapse throws frames away. Taking 1 of every 10 frames results in a 10x speed increase. Unfortunately, speeding up a head mounted camera often leads to a video so bouncy it can’t be watched without an air sickness bag handy. [Johannes Kopf], [Michael Cohen], and [Richard Szeliski] at Microsoft Research have come up with a novel solution to this problem with Hyperlapse.

Hyperlapse photography is not a new term. Typically, hyperlapse films require careful planning, camera rigs, and labor-intensive post-production to achieve a usable video. [Johannes] and team have thrown computer vision and graphics algorithms at the problem. The results are nothing short of amazing.

The full details are available in the team’s report (35MB PDF warning). To obtain usable data, the fisheye lenses often used on these cameras must be calibrated. The team accomplished that with the OCamCalib toolbox. Imported video is broken down frame by frame. Using structure from motion algorithms, hyperlapse creates a 3D models of the various scenes in the video. With the scenes in this virtual world, the camera can be moved and aimed at will. The team’s algorithms then pick a smooth path that follows the original cameras trajectory. Once the camera’s position is known, it’s simply a matter of rendering the final video.

The results aren’t perfect. The mountain climbing scenes show some artifacts caused by the camera frame rate and exposure changing due to the varied lighting conditions. People appear and disappear in the bicycling portion of the video.

One thing the team doesn’t mention is how long the process takes. We’re sure this kind of rendering must require some serious time and processing power. Still, the output video is stunning.

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Timelapse Photos for All!

Find yourself wanting to do some timelapse but lacking the equipment? Why not build your own time lapse rig as seen in instructables how to by [Constructer].  To accomplish this, all you will need is a little wood, screws, a motor, and some batteries.  The how-to says you can add extra voltage to speed up the rate of taking photos, or conversely reduce voltage to slow it down.  We especially like the simplicity of this mechanical approach. No timers, no programming, only a motor.  One downfall of this simplistic approach, however is that your “gap” between pictures will increase as your battery dies.

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Timelapse circuit for point and shoot cameras

[Andyk75] has done some fantastic work documenting his timelapse addition to his digital camera.  Most of the more expensive models of cameras have a remote shutter release, but the point and shoot jobs usually don’t. He decided to add the ability to turn the camera on, then shoot a picture, then turn it back off. Pretty smart, since these things tend to eat batteries pretty quickly if left on.  He is using an ATtiny24 for the brains, but the circuit should be pretty adaptable to others. The final piece has several features, like the ability to change the length of time between shots and automatically shut down when it gets too dark outside to continue. He has posted the schematics as well as the board layouts if you can find them amongst the ads in instructibles. You can check out a video of a sunset taken with this camera after the break.

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Toyaanisqatsi: time lapse control using LEGO parts

A simple panning motion can add impact to the already-dramatic effect of time lapse photography. To accomplish this, frugal cinematographers sometimes build [Rube Goldberg] contraptions from clock motors, VCR parts or telescope tracking mounts. Hack a Day reader [Stephan Martin] has assembled a clever bargain-basement system using an Arduino-driven stepper motor and a reduction gear system built up from LEGO Technic parts, along with some Processing code on a host PC to direct the show.

While the photography is a bit crude (using just a webcam), [Stephan’s] underlying motion control setup might interest budding filmmakers with [Ron Fricke] aspirations but Top Ramen budgets. What’s more, unlike rigid clock motor approaches, software control of the camera mount has the potential for some interesting non-linear, fluid movements.

DS + 50D timelapse examples

We covered [Steve Chapman]’s Nintendo DS control for his Canon DSLR in September. He’s since improved the software so that it has a timer for sunset/sunrise amongst other things. He also shot about 30GB worth of timelapse images while in Vancouver and assembled a couple test videos. He’s still working out the processing to take full advantage of the 15megapixel images. We look forward to future results since YouTube is now using a much larger player for high def content.