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They may be a little late to be competitive for upcoming devices: while compared to other structured-light or RToF sensors this is attractive, the new game in town is DToF sensors, the first commercial one quietly being plopped into the recent iPad Pro.
RToF like that used in the Kinect 2 relies of relative phase difference between pixel pairs (along with a synchronised illuminator) to watch incoming light shift in and out or relative sync (via relative brightness using phase offset). That gives you a relative depth value vs. the wavelength as it propagates out, but does not give you any absolute depth values. Like with relative-offset structured light approaches (e.g. Kinect 1) there is still a modelling and estimation stage required to turn that into an estimated depth map. Same with this sensor.
DToF, or Direct Time of Flight (AKA Flash LIDAR) is a different beast. Here, a pulse is sent out and each pixel measures the /actual true flight time/ between emission and reception. This not only gives you absolute depth values, but lets you do some VERY cool tricks. For example, you can gate your sensor to pick up the 'furthest' value for each pixel, which allows you to see through dense fog or dust (as the early reflections from intervening particles are discarded), or measure the front and back surfaces of translucent objects. DToF has previously been the domain of rather expensive sensors used for geospatial mapping (those fancy point-clouds taken by drones of forests revealing the forest floor straight through the treetops are produced by pulse LIDAR).
Um, the iPad Pro sensor is remarkably low resolution, when compared to the DepthIQ sensor. It's design is more suited for AR and room scale, and is not even close to per pixel, as you imagine it can be.
Of course, but your original assertion was that you could find per-pixel depth information when the current implementation only gives you depth information for the center pixel in 20 or so radius.
The main problems with any structured-light or ToF solution is they don't contend well with daylight, and have limited range. Passive solutions, like stereo or this, have no inherent range limit and work best in good lighting.
DToF does not have the same light pollution sensitivity as RToF systems. Because they rely on active temporal gating, they actively reject incident light.
Like other depth sensing approaches, DToF relies on an additional depth sensor and special lighting. Our approach utilizes the same sensor used for capturing the 2D color image. Due to cost and size, it will be difficult for the dedicated depth sensor based approaches to extend from high end platforms to a broader, more general adoption. Airy3D’s approach can bring depth capture to a much broader swath of camera deployments.
Hooray for 19th century science being turned into 21st century high-tech!
When you say no limit to resolution, I guess that refers to x and y distribution of z values.
What about z range and precision? Do you have to stagger or dedicate x and y pixels to sense at different z-depths via distinct patterns, or are they all the same? From the video the depth resolution seems much coarser than pixel size, which would hint at a z partitioning.
The number of Z pixels is selectable, the video you were seeing was 1 Z pixels for every 4x4 (16) X,Y pixels, mostly selected for convenience as it produces a 1Mp depth image on a 16MP 2D image.. We can scale the Z pixel resolution from 1 Z pixel for every X,Y pixel down to whatever ratio fits your use case. The density of Z pixels can also be adapted dynamically within a frame.
Excellent article thanks Andrei. I'm new to this area but your technical explanation was clear and easy to follow. It struck the right balance between not skimming over details too much (like Wired does) but not going too deep into the optics.
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wishgranter - Thursday, June 4, 2020 - link
Interesting technology...mkozakewich - Wednesday, June 10, 2020 - link
There is no way that's 3.5%. More like 35%!evacdesilets - Sunday, June 14, 2020 - link
Make money online from home extra cash more than $18k to $21k. Start getting paid every month Thousands Dollars online. I have received $26K in this month by just working online from home in my part time.every person easily do this job by just open this link and follow details on this page to get started... WWW.iⅭash68.ⅭＯⅯedzieba - Thursday, June 4, 2020 - link
They may be a little late to be competitive for upcoming devices: while compared to other structured-light or RToF sensors this is attractive, the new game in town is DToF sensors, the first commercial one quietly being plopped into the recent iPad Pro.RToF like that used in the Kinect 2 relies of relative phase difference between pixel pairs (along with a synchronised illuminator) to watch incoming light shift in and out or relative sync (via relative brightness using phase offset). That gives you a relative depth value vs. the wavelength as it propagates out, but does not give you any absolute depth values. Like with relative-offset structured light approaches (e.g. Kinect 1) there is still a modelling and estimation stage required to turn that into an estimated depth map. Same with this sensor.
DToF, or Direct Time of Flight (AKA Flash LIDAR) is a different beast. Here, a pulse is sent out and each pixel measures the /actual true flight time/ between emission and reception. This not only gives you absolute depth values, but lets you do some VERY cool tricks. For example, you can gate your sensor to pick up the 'furthest' value for each pixel, which allows you to see through dense fog or dust (as the early reflections from intervening particles are discarded), or measure the front and back surfaces of translucent objects. DToF has previously been the domain of rather expensive sensors used for geospatial mapping (those fancy point-clouds taken by drones of forests revealing the forest floor straight through the treetops are produced by pulse LIDAR).
michael2k - Thursday, June 4, 2020 - link
Um, the iPad Pro sensor is remarkably low resolution, when compared to the DepthIQ sensor. It's design is more suited for AR and room scale, and is not even close to per pixel, as you imagine it can be.close - Friday, June 5, 2020 - link
Indeed, this is a good visual comparison between the iPad Pro sensor and even FaceID: https://image-sensors-world.blogspot.com/2020/03/t...edzieba - Friday, June 5, 2020 - link
There's a lot more to a depth sensors utility than just resolution.https://www.i-micronews.com/with-the-apple-ipad-li...
michael2k - Friday, June 5, 2020 - link
Of course, but your original assertion was that you could find per-pixel depth information when the current implementation only gives you depth information for the center pixel in 20 or so radius.BedfordTim - Friday, June 5, 2020 - link
Interesting. Another site had linked Apple's patent to an ST MEMS device.mode_13h - Friday, June 5, 2020 - link
The main problems with any structured-light or ToF solution is they don't contend well with daylight, and have limited range. Passive solutions, like stereo or this, have no inherent range limit and work best in good lighting.edzieba - Friday, June 5, 2020 - link
DToF does not have the same light pollution sensitivity as RToF systems. Because they rely on active temporal gating, they actively reject incident light.Airy3D - Tuesday, June 16, 2020 - link
Like other depth sensing approaches, DToF relies on an additional depth sensor and special lighting. Our approach utilizes the same sensor used for capturing the 2D color image. Due to cost and size, it will be difficult for the dedicated depth sensor based approaches to extend from high end platforms to a broader, more general adoption. Airy3D’s approach can bring depth capture to a much broader swath of camera deployments.abufrejoval - Thursday, June 4, 2020 - link
Hooray for 19th century science being turned into 21st century high-tech!When you say no limit to resolution, I guess that refers to x and y distribution of z values.
What about z range and precision? Do you have to stagger or dedicate x and y pixels to sense at different z-depths via distinct patterns, or are they all the same? From the video the depth resolution seems much coarser than pixel size, which would hint at a z partitioning.
Airy3D - Tuesday, June 16, 2020 - link
The number of Z pixels is selectable, the video you were seeing was 1 Z pixels for every 4x4 (16) X,Y pixels, mostly selected for convenience as it produces a 1Mp depth image on a 16MP 2D image.. We can scale the Z pixel resolution from 1 Z pixel for every X,Y pixel down to whatever ratio fits your use case. The density of Z pixels can also be adapted dynamically within a frame.Tomatotech - Friday, June 5, 2020 - link
Excellent article thanks Andrei. I'm new to this area but your technical explanation was clear and easy to follow. It struck the right balance between not skimming over details too much (like Wired does) but not going too deep into the optics.sonicmerlin - Saturday, June 6, 2020 - link
Cool. Could this be used in a Face ID camera to get rid of the notch or at least shrink its size?Airy3D - Tuesday, June 16, 2020 - link
Yes, Airy3D’s technology can be embedded in the front facing camera, meaning it can enable depth without changes to the platform’s industrial design.