A Dropcam will run you about $150. Price out a Raspberry Pi, camera sensor, and a CCTV camera housing found on eBay, and it starts to look like there may be a cheaper replacement for a Dropcam sitting around on workbenches, if only someone can figure out the software. [Antoine] did just that, giving any Raspberry Pi the ability to stream H.264 video over a network.
[Antoine]’s software is based on the raspivid tool distributed from the foundation, but that only takes care of capturing and encoding H.264 video from the camera sensor. To add IP camera support, the Live555 RTSP library was mixed in and combined to stream video over the Raspi’s network connection.
[Ben] has written all sorts of code and algorithms to filter, sort, and convolute images, and also a few gadgets that were meant to be photographed. One project that hasn’t added a notch to his soldering iron was a camera. The easiest way to go about resolving this problem would be to find some cardboard and duct tape and built a pinhole camera. [Ben] wanted a digital camera. Not any digital camera, but a color digital camera, and didn’t want to deal with pixel arrays or lenses. Impossible, you say? Not when you have a bunch of integral transforms in your tool belt.
[Ben] is only using a single light sensor that outputs RGB values for his camera – no lenses are found anywhere. If, however, you scan a scene multiple times with this sensor, each time blocking a portion of the sensor’s field of view, you could reconstruct a rudimentary, low-resolution image from just a single light sensor. If you scan and rotate this ‘blocking arm’ across the sensor’s field of view, reconstructing the image is called a Radon transform, something [Ben] has used a few times in his studies.
[Ben]’s camera consists of the Adafruit RGB light sensor, an Arduino, a microSD card, a few servos, and a bunch of printed parts. The servos are used to scan and rotate the ‘blocking arm’ across the sensor for each image. The output of the sensor is saved to the SD card and moved over to the computer for post-processing.
After getting all the pixel data to his laptop, [Ben] plotted the raw data. The first few pictures were of a point source of light – a lamp in his workspace. This resulted in exactly what he expected, a wave-like line on an otherwise blank field. The resulting transformation kinda looked like the reference picture, but for better results, [Ben] turned his camera to more natural scenes. Pointing his single pixel camera out the window resulted in an image that looked like it was taken underwater, through a piece of glass smeared with Vaseline. Still, it worked remarkably well for a single pixel camera. Taking his camera to the great outdoors provided an even better reconstructed scene, due in no small part to the great landscapes [Ben] has access to.
On the hardware side, the dolly carries the camera on a rail that is set up on a slant. The camera starts on one side and moves up and towards the otherside which creates a unique effect in the time-lapse. The rig is driven by a stepper motor, and rides on some pretty fancy bearings. The two cameras [Bryce] plans to use are a Canon T2i and a EOS-M which sit on the top from a tripod.
The software and electronics side is interesting as well. Instead of the usual Arduino, [Bryce] opted for controlling the rig through Android and a IOIO board. This gives the project a lot of options for communications, including Bluetooth. The whole thing is powered by a 19V battery pack. If you’re looking for something a little simpler, you might want to check out the egg timer for time lapse! Check out the video of [Bryce]’s rig in action after the break.
If you want to take a photograph with a professional look, proper lighting is going to be critical. [Richard] has been using a commercial lighting solution in his studio. His Lencarta UltraPro 300 studio strobes provide adequate lighting and also have the ability to have various settings adjusted remotely. A single remote can control different lights setting each to its own parameters. [Richard] likes to automate as much as possible in his studio, so he thought that maybe he would be able to reverse engineer the remote control so he can more easily control his lighting.
[Richard] started by opening up the remote and taking a look at the radio circuitry. He discovered the circuit uses a nRF24L01+ chip. He had previously picked up a couple of these on eBay, so his first thought was to just promiscuously snoop on the communications over the air. Unfortunately the chips can only listen in on up to six addresses at a time, and with a 40-bit address, this approach may have taken a while.
Not one to give up easily, [Richard] chose a new method of attack. First, he knew that the radio chip communicates to a master microcontroller via SPI. Second, he knew that the radio chip had no built-in memory. Therefore, the microcontroller must save the address in its own memory and then send it to the radio chip via the SPI bus. [Richard] figured if he could snoop on the SPI bus, he could find the address of the remote. With that information, he would be able to build another radio circuit to listen in over the air.
Using an Open Logic Sniffer, [Richard] was able to capture some of the SPI communications. Then, using the datasheet as a reference, he was able to isolate the communications that stored information int the radio chip’s address register. This same technique was used to decipher the radio channel. There was a bit more trial and error involved, as [Richard] later discovered that there were a few other important registers. He also discovered that the remote changed the address when actually transmitting data, so he had to update his receiver code to reflect this.
The receiver was built using another nRF24L01+ chip and an Arduino. Once the address and other registers were configured properly, [Richard’s] custom radio was able to pick up the radio commands being sent from the lighting remote. All [Richard] had to do at this point was press each button and record the communications data which resulted. The Arduino code for the receiver is available on the project page.
[Richard] took it an extra step and wrote his own library to talk to the flashes. He has made his library available on github for anyone who is interested.
[Andy] wanted to take a few at sunrise, but waking up before sunrise has obvious problems associated with it. Instead, he built a device that calculates the local sunrise time, snaps a picture, and goes to sleep until the next morning.
The camera used for the project was an old Canon point and shoot, chosen for the ability to load CHDK firmware. Other electronics included an Arduino pro mini, a LiPo battery and charger board, real time clock, and an old Nokia LCD for the user interface.
There’s quite a bit of code that goes into figuring out when the sun will rise each day, but once that’s figured out, all [Andy] has to do is take the camera somewhere pretty, point it East, and record a few days worth of sunrises. When put into a ‘game camera’ enclosure, its rugged enough to stand up to everything except a thief, and has enough battery power for a few weeks worth of sunrises.
After 20 or so years of development, digital cameras may soon be superior to film in almost every way, but there are a few niches where film cameras reign supreme. Large format cameras, for example, are able to produce amazing images, but short of renting one for thousands of dollars a day, you’ll probably never get your hands on one. For his entry to The Hackaday Prize, [Jimmy.c..alzen] decided to build a digital large format camera, using an interesting device you don’t see used very often these days – a linear CCD.
[Jimmy]’s camera is built around a TAOS TS1412S, a linear CCD that is able to capture a line of light 1536 pixels across. The analog values are clocked out from this chip in sequence, going straight into an Arduino Due for processing, saving, and displaying on a small screen.
Inside the camera, the sensor is on a pair of rails and driven across the focal plane with the help of a stepper motor. The effect is something like the flatbed scanner to camera conversions we’ve seen in the past, but [Jimmy] is able to adjust the exposure of the camera simply by changing the integration time of the sensor. He can also change the delay between scanning each column of pixels, making for some really cool long-exposure photography techniques; one side of an image could be captured at noon, while the other side could be from a beautiful sunset. That’s something you just can’t do otherwise without significant digital manipulation outside the camera.
The project featured in this post is an entry in The Hackaday Prize. Build something awesome and win a trip to space or hundreds of other prizes.
[David Schwarz] whipped up this moving time-lapse camera rig and won himself a sweet Nikon setup. You might remember our post about the Nikon Make:The Shot Challenge. [David] saw our post, and started thinking about what he wanted to enter. Like a true engineer, he finally came up with his idea with just 3 days left in the contest.
[David] wanted to build a moving time-lapse rig, but he didn’t have the aluminum extrusion rails typically used to build one. He did have some strong rope though, as well as a beefy DC motor with a built-in encoder. [David] mounted a very wide gear on the shaft of the motor, then looped the rope around the gear and two idler pulleys to ensure the gear would have a good bite on the rope. The motor is controlled by an Arduino, which also monitors the encoder to make sure the carriage doesn’t move too far between shots.
[David] built and tested his rig over a weekend. On Monday morning, he gave the rig its first run. The video came out pretty good, but he knew he could get a better shot. That’s when Murphy struck. The motor and controller on his rig decided to give up the ghost. With the contest deadline less than 24 hours away, [David] burned the midnight oil and replaced his motor and controller.
Tuesday morning, [David] pulled out his trump card – a trip to Tally Lake in Montana, USA. The equipment worked perfectly, and nature was cooperating too. The trees, lake, and the shadows on the mountains in the background made for an incredible shot. Once the time-lapse photos were in the can, [David] rushed home, stitched and stabilized the resulting video. He submitted his winning entry with just 2 hours to spare.
Click past the break for more on [David’s] time-lapse rig, and to see his final video.