New Part Day: Onion Tau LiDAR Camera

The Onion Tau LiDAR Camera is a small, time-of-flight (ToF) based depth-sensing camera that looks and works a little like a USB webcam, but with  a really big difference: frames from the Tau include 160 x 60 “pixels” of depth information as well as greyscale. This data is easily accessed via a Python API, and example scripts make it easy to get up and running quickly. The goal is to be an affordable and easy to use option for projects that could benefit from depth sensing.

When the Tau was announced on Crowd Supply, I immediately placed a pre-order for about $180. Since then, the folks at Onion were kind enough to send me a pre-production unit, and I’ve been playing around with the device to get an idea of how it acts, and to build an idea of what kind of projects it would be a good fit for. Here is what I’ve learned so far.

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OpenCV And Depth Camera Spots Weeds

Using vision technology to identify weeds in agriculture is an area of active development, and a team of researchers recently shared their method of using a combination of machine vision plus depth information to identify and map weeds with the help of OpenCV, the open-source computer vision library. Agriculture is how people get fed, and improving weed management is one of its most important challenges.

Many current efforts at weed detection and classification use fancy (and expensive) multispectral cameras, but PhenoCV-WeedCam relies primarily on an OAK-D stereo depth camera. The system is still being developed, but is somewhat further along than a proof of concept. The portable setups use a Raspberry Pi, stereo camera unit, power banks, an Android tablet for interfacing, and currently require an obedient human to move and point them.

It’s an interesting peek at the kind of hands-on work that goes into data gathering for development. Armed with loads of field data from many different environments, the system can use the data to identify grasses, broad leaf plants, and soil in every image. This alone is useful, but depth information also allows the system to estimate overall plant density as well as try to determine the growth center of any particular plant. Knowing that a weed is present is one thing, but to eliminate it with precision — for example with a laser or mini weed whacker on a robot arm — knowing where the weed is actually growing from is an important detail.

PhenoCV-WeedCam (GitHub repository) is not yet capable of real-time analysis, but the results are promising and that’s the next step. The system currently must be carried by people, but could ultimately be attached to a robotic platform made specifically to traverse fields.

Kinect Gave Us A Preview Of The Future, Though Not The One It Intended

This holiday season, the video game industry hype machine is focused on building excitement for new PlayStation and Xbox consoles. Ten years ago, a similar chorus of hype reached a crescendo with the release of Xbox Kinect, promising to revolutionize how we play. That vision never panned out, but as [Daniel Cooper] of Engadget pointed out in a Kinect retrospective, it premiered consumer technologies that impacted fields far beyond gaming.

Kinect has since withdrawn from the gaming market, because as it turns out gamers are quite content with handheld controllers. This year’s new controllers for a PlayStation or Xbox would be immediately familiar to gamers from ten years ago. Even Nintendo, whose Wii is frequently credited as motivation for Microsoft to develop the Kinect, have arguably taken a step back with Joy-cons of their Switch.

But the Kinect’s success at bringing a depth camera to consumer price levels paved the way to explore many ideas that were previously impossible. The flurry of enthusiastic Kinect hacking proved there is a market for depth camera peripherals, leading to plug-and-play devices like Intel RealSense to make depth-sensing projects easier. The original PrimeSense technology has since been simplified and miniaturized into Face ID unlocking Apple phones. Kinect itself found another job with Microsoft’s HoloLens AR headset. And let’s not forget the upcoming wave of autonomous cars and drones, many of which will see their worlds via depth sensors of some kind. Some might even be equipped with the latest sensor to wear the Kinect name.

Inside the Kinect was also one of the earliest microphone arrays sold to consumers. Enabling the Kinect to figure out which direction a voice is coming from, and isolate it from other noises in the room. Such technology were previously the exclusive domain of expensive corporate conference room speakerphones, but now it forms the core of inexpensive home assistants like an Amazon Echo Dot. Raising the bar so much that hacks needed many more microphones just to stand out.

With the technology available more easily elsewhere, attrition of a discontinued device is reflected in the dwindling number of recent Kinect hacks on these pages. We still see a cool project every now and then, though. As the classic sensor bar itself recedes into history, others will take its place to give us depth sensing and smart audio. But for many of us, Kinect was the ambitious videogame peripheral that gave us our first experience.

Machine Vision Keeps Track Of Grubby Hands

Can you remember everything you’ve touched in a given day? If you’re being honest, the answer is, “Probably not.” We humans are a tactile species, with an outsized proportion of both our motor and sensory nerves sent directly to our hands. We interact with the world through our hands, and unfortunately that may mean inadvertently spreading disease.

[Nick Bild] has a potential solution: a machine-vision system called Deep Clean, which monitors a scene and records anything in it that has been touched. [Nick]’s system uses Jetson Xavier and a stereo camera to detect depth in a scene; he built his camera from a pair of Raspberry Pi cams and a Pi 3B+, but other depth cameras like a Kinect could probably do the job. The idea is to watch the scene for human hands — OpenPose is the tool he chose for that job — and correlate their depth in the scene with the depth of objects. Touch a doorknob or a light switch, and a marker is left on the scene. The idea would be that a cleaning crew would be able to look at the scene to determine which areas need extra attention. We can think of plenty of applications that extend beyond the current crisis, as the ability to map areas that have been touched seems to be generally useful.

[Nick] has been getting some mileage out of that Xavier lately — he’s used it to build an AI umpire and shades that help you find lost stuff. Who knows what else he’ll find to do with them during this time of confinement?

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Handheld 3D Scanning, Using Raspberry Pi 4 And Intel RealSense Camera

Raspberry Pi 4 (with USB 3.0) and Intel RealSense D415 depth sensing camera.

When the Raspberry Pi 4 came out, [Frank Zhao] saw the potential to make a realtime 3D scanner that was completely handheld and self-contained. The device has an Intel RealSense D415 depth-sensing camera as the main sensor, which uses two IR cameras and an RGB camera along with the Raspberry Pi 4. The Pi uses a piece of software called RTAB-Map — intended for robotic applications — to take care of using the data from the camera to map the environment in 3D and localize itself within that 3D space. Everything gets recorded in realtime.

This handheld device can act as a 3D scanner because the data gathered by RTAB-Map consists of a point cloud of an area as well as depth information. When combined with the origin of the sensing unit (i.e. the location of the camera within that area) it can export a point cloud into a mesh and even apply a texture derived from the camera footage. An example is shown below the break.
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New Kinect Sensor Switch Focus From Gamers To Developers

Microsoft’s Kinect may not have found success as a gaming peripheral, but recognizing that a depth sensor is too cool to leave for dead, development continued even after Xbox gaming peripherals were discontinued. This week their latest iteration emerged and we can get it in the form of Azure Kinect DK. This is a developer’s kit focused on exploring new applications for this technology, not a gaming peripheral we had to hack before we could use in our own projects.

Packaged into a peripheral that plugs into a PC via USB-C, it is more than the core depth sensor module announced last year but less than a full consumer product. Browsing its 10-page specification (PDF) with comparisons to second generation Kinect sensor bar, we see how this technology has evolved. Physical size and weight has dropped, as has power consumption. Auxiliary capabilities has improved with an expanded microphone array, IMU with gyro in addition to accelerometer, and the RGB camera has been upgraded to 4K resolution.

But the star of the show is a new continuous-wave time-of-flight depth sensor, presented at the 2018 IEEE ISSCC conference. (Full text requires IEEE membership, but a digest form is available via ResearchGate.) Among its many advancements, we expect the biggest impact to be its field of view. Default of 75 x 65 degrees is already better than its predecessors (64 x 45 for first generation Kinect, 70 x 60 for second) but there is an option to trade resolution for coverage by switching to a wide-angle mode of 120 x 120 degrees. Significantly wider than other depth cameras like Intel’s RealSense D400 series or Occipital’s Structure.

Another interesting feature is built-in synchronization. Many projects using multiple Kinect sensors ran into problems because they interfered with each other. People hacked around the problem, of course, but now they don’t have to: commodity 3.5 mm jacks allow multiple Azure Kinect DK to be daisy chained together so they play nicely and take turns.

From its name we were worried this product would require Microsoft’s Azure cloud service in some way and be crippled without it. Based on information released so far, it appears developers have access to all the same data streams as previous sensors. Azure tie-in takes the form of optional SDKs that make it easier to do things like upload data for processing in Azure cloud-based recognition services.

And finally, Azure Kinect DK’s price tag of $399 is significantly higher than a Kinect game peripheral, but it is a low volume product for developers. Perhaps high volume consumer products built on this technology will cost less, but that remains to be seen. In the meantime, you have alternative tools for solving similar problems. For example if you are building your own AR headset, you might use Intel’s latest RealSense camera for vision based inside-out motion tacking.

Microsoft Kinect Episode IV: A New Hope

The history of Microsoft Kinect has been of a technological marvel in search of the perfect market niche. Coming out of Microsoft’s Build 2018 developer conference, we learn Kinect is making another run. This time it’s taking on the Internet of Things mantle as Project Kinect for Azure.

Kinect was revolutionary in making a quality depth camera system available at a consumer price point. The first and second generation Kinect were peripherals for Microsoft’s Xbox gaming consoles. They wowed the world with possibilities and, thanks in large part to an open source driver bounty spearheaded by Adafruit, Kinect found an appreciative audience in robotics, interactive art, and other hacking communities. Sadly its novelty never translated to great success in its core gaming market and Kinect as a gaming peripheral was eventually discontinued.

For its third-generation, Kinect retreated from gaming and found a role in Microsoft’s HoloLens AR headset running “backwards”: tracking user’s environment instead of user’s movement. The high cost of a HoloLens put it out of reach of most people, but as a head-mounted battery-powered device, it pushed Kinect technology to shrink in physical size and power consumption.

This upcoming fourth generation takes advantage of that evolution and the launch picture is worth a thousand words all on its own: instead of a slick end-user commercial product, we see a populated PCB awaiting integration. The quoted power draw of 225-950mW is high by modern battery-powered device standards but undeniably a huge reduction from previous generations’ household AC power requirement.

Microsoft’s announcement heavily emphasized how this module will work with their cloud services, but we hope it can be persuaded to run independently from Microsoft’s cloud just as its predecessors could run independent of game consoles. This will be a big factor for adoption by our community, second only to the obvious consideration of price.

[via Engadget]