New Drivers For Ancient Webcam

For those of us who are a little older, the 90s seem like they were just a few years ago. The younger folks might think that the 90s were ancient history though, and they might be right as we’ve been hearing more bands like Pearl Jam and The Offspring playing on the classic rock stations lately. Another example of how long ago the 90s were is taking a look at the technological progress that has happened since then through the lens of things like this webcam from 1999, presuming you load up this custom user space driver from [benjojo].

Thankfully the driver for this infamous webcam didn’t need to be built completely from scratch. There’s a legacy driver available for Windows XP which showed that the camera still physically worked, and there’s also a driver for Linux which was used as a foundation to start working from. From there a USB interface was set up which allowed communication to the device. Not a simple task, but apparently much easier than the next steps which involve actually interpreting the information coming from the webcam. This is where a background in digital signal processing is handy to have. First, the resolution and packet size were sorted out which led to a somewhat recognizable image. From there a single monochrome image was pieced together, and then after deconstructing a Bayer filter and adding color, the webcam is back to its former 90s glory.

[benjojo] has hosted all of the code for this project on a GitHub page for anyone who still has one of these webcams sitting around in the junk drawer. The resolution and color fidelity are about what we’d expect for a 25-year-old device that predates Skype, Facebook, Wikipedia, and Firefox. And, while there are still some things that need to be tweaked such as the colors, white balance, and exposure, once that is sorted out the 90s and early 00s nostalgia is free to flood in.

Keeping An Eye On Heating Oil

Energy costs around the world are going up, whether it’s electricity, natural gas, or gasoline. This is leading to a lot of people looking for ways to decrease their energy use, especially heading into winter in the Northern Hemisphere. As the saying goes, you can’t manage what you can’t measure, so [Steve] has built this system around monitoring the fuel oil level for his home’s furnace.

Fuel oil is an antiquated way of heating, but it’s fairly common in certain parts of the world and involves a large storage tank typically in a home’s basement. Since the technology is so dated, it’s not straightforward to interact with these systems using anything modern. This fuel tank has a level gauge showing its current percentage full. A Raspberry Pi is set up nearby with a small camera module which monitors the gauge, and it runs OpenCV to determine the current fuel level and report its findings.

Since most fuel tanks are hidden in inconvenient locations, it makes checking in on the fuel level a breeze and helps avoid running out of fuel during cold snaps. [Steve] designed this project to be reproducible even if your fuel tank is different than his. You have other options beyond OpenCV as well; this fuel tank uses ultrasonic sensors to measure the fuel depth directly.

Machine Learning Does Its Civic Duty By Spotting Roadside Litter

If there’s one thing that never seems to suffer from supply chain problems, it’s litter. It’s everywhere, easy to spot and — you’d think — pick up. Sadly, most of us seem to treat litter as somebody else’s problem, but with something like this machine vision litter mapper, you can at least be part of the solution.

For the civic-minded [Nathaniel Felleke], the litter problem in his native San Diego was getting to be too much. He reasoned that a map of where the trash is located could help municipal crews with cleanup, so he set about building a system to search for trash automatically. Using Edge Impulse and a collection of roadside images captured from a variety of sources, he built a model for recognizing trash. To find the garbage, a webcam with a car window mount captures images while driving, and a Raspberry Pi 4 runs the model and looks for garbage. When roadside litter is found, the Pi uses a Blues Wireless Notecard to send the GPS location of the rubbish to a cloud database via its cellular modem.

Cruising around the streets of San Diego, [Nathaniel]’s system builds up a database of garbage hotspots. From there, it’s pretty straightforward to pull the data and overlay it on Google Maps to create a heatmap of where the garbage lies. The video below shows his system in action.

Yes, driving around a personal vehicle specifically to spot litter is just adding more waste to the mix, but you’d imagine putting something like this on municipal vehicles that are already driving around cities anyway. Either way, we picked up some neat tips, especially those wireless IoT cards. We’ve seen them used before, but [Nathaniel]’s project gives us a path forward on some ideas we’ve had kicking around for a while.

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You Draw It, CNC Cuts It

[Jamie] aka [vector76] hit us with a line-tracing plugin for OctoPrint that cuts out whatever 2D shape you draw on a piece of wood. The plugin lets you skip the modeling step entirely, going straight from a CNC-mounted webcam that reads your scribbles and gives you a Gcode toolpath in return. The code is on GitHub and there’s a demo video embedded below.

Under the hood, OpenCV is doing a lot of the image processing, including line detection, and the iterative “find the line” and “move the toolhead” steps really show off what computer vision can do. It starts off with a fiducial arrow for scale and orientation, then it mores the webcam around the scene. The user can enter the usual milling parameters: speeds, feeds, depth of cut, tool offset, milling direction, etc. And then it gets to work.

Right now, it’s limited to paths with non-crossing lines, and probably with good contrast and a nice dark line — all the usual CV restrictions. But mounting a webcam to a CNC toolhead and using it for various pathing problems really opens up tons of possibilities: visual homing, workpiece edge finding, copying parts, custom fitting odd shapes, and more. This project is clearly an invitation to keep on hacking, an appetizer. Once you see the girl pirate robot that [Jamie]’s daughter made, you’ll get the idea.

We’ve seen a similar OpenCV approach used for center-finding bore holes, but while we’ve seen a few webcams used with laser cutters, the CNC mill applications seem largely untapped. Let us know in the comments if you’ve got some other good examples.

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Morse Keyboard Communicates With The Blink Of An Eye

Most of us use our hands to interface with computers, but the human body is capable of many types of input other than that of fingers and feet. But what about people who can’t use their extremities and don’t have a voice? For their sake, it’s time to get creative.

[Michael Paul Coder] has made a way to type simply by blinking in Morse code. Those of you with long memories may recall Lucid Scribe, where he was attempting to document lucid dreaming experiments by detecting rapid eye movements with an accelerometer and triggering his computer to play music. This would in turn notify [Michael] that he was in fact dreaming and was safe to tie a cape around his neck and take a flying leap from a tall building.

Whereas [Michael]’s creation needed a commercial EEG device before, he’s now made it work with just an old webcam thanks to the new trans-consciousness messaging protocol, which operates by using facial detection and then interpreting the amount of changed pixels between video frames. Be sure to check it out in action after the break.

You know how much we love assistive technology around here — just two years ago, the Byte took top honors in The Hackaday Prize.

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Dominate Video Calls With Game Boy Camera Webcam

We can’t promise it will all be positive, but there’s no question you’ll be getting plenty of attention when you join a video call using the Game Boy Camera. Assuming they recognize you, anyway. The resolution and video quality of the 1998 toy certainly hasn’t aged very well, and that’s before it gets compressed and sent over the Internet.

From a technical standpoint, this one is actually pretty simple, if rather convoluted. [RetroGameCouch] hasn’t modified the Game Boy Camera in any way, he’s just connected it to the Super Game Boy, which in turn is slotted into a Super Nintendo. From there the video output of the SNES is passed through an HDMI converter, and finally terminates in a cheap HDMI capture device. His particular SNES has been modified with component video, but on the stock hardware you’ll have to be content with composite.

The end result of all these adapters and cables is that the live feed from the Game Boy Camera, complete with the Super Game Boy’s on-screen border, is available on the computer as a standard USB video device that can be used with whatever program you wish. If you’re more interested in recovering still images, we’ve recently seen a project that lets you pull images from the Game Boy Camera over WiFi.

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Friendly Webcam Robot Keeps An Eye On Privacy

Wouldn’t it be nice if every webcam had a hardware switch? Especially for those built-in webcams like the one in your laptop. Since they don’t have switches yet, we’re just stuck trying to remember to turn them off or re-apply the sticker after every meeting. [Becky Stern] was tired of trying to remember to blind the all-seeing eye, and decided to make a robot companion that would do it for her.

Essentially, a servo-driven, 3D-printed eyelid covers the eye’s iris and also the web cam directly underneath. At first, we though [Becky] had liberated the business parts of a cheap webcam and built it into the eyeball, but this is far less intrusive. The eyeball simply sits atop the monitor, and [Becky] can control the eyelid two ways: she can set a timer with the potentiometer to close it automatically after some number of minutes, or else do it on demand using the momentary button. We’d love to see it tied directly to Zoom and or whatever else [Becky] uses regularly. Be sure to check out the build and demo video after the break to see it in action.

We love this cute and friendly reminder that the camera could be watching us. It’s way less creepy than this realistic eyeball webcam that looks around and blinks.

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