The ability to see maps in buildings and landscapes in 3D makes following along considerably easier than with just 2D. So researchers at the University of Washington have made generating 3D models of a given location dead simple using custom software and nothing more than a webcam timelapse video of the spot captured on a sunny day.
As the sun moves across the sky it creates ever-changing shadows on every surface—from a towering skyscraper’s silhouette on the ground, to subtle architectural details. And by analyzing timelapse footage filmed across an entire day, the software’s algorithm is able to extrapolate the shape and positions of every structure in frame.
To work its magic the program does need to know the exact position of the camera using GPS data so it can calculate how high the sun was in the sky, and the time of day for every single frame. But once a scene is processed it’s able to spit out a 3D model that could then be added to existing databases such as the one used by Google in its map app. So eventually anyone who knows how to point a camera and hit record can make a contribution for the area where they live. [Washington University via NewScientist]
Zacuto USA goes to great lengths to compare nine HD video cameras in The Revenge Of The Great Camera Shootout 2012. With all the footage shot and judged, the camera most favored by many accomplished filmmakers—including Francis Ford Coppola—was a huge surprise.
The showdown was a sequel to the Great Camera Shootout of 2010 and 2011, which focused on raw technical performance of cameras from Canon, Sony, Panasonic, RED, and others. This year, rather than straight pixel-peeping, Zacuto paired each camera with a professional cinematographer and a pre-staged scene.
The contenders included a wide range of cameras, ranging from the $65,000 Sony F65, right down to the iPhone 4. Audiences of filmmakers around the world were shown each camera’s results, the names of each camera remaining a mystery. The most favored machine, to the shock of many, turned out to be the $700 Panasonic GH2 micro four-thirds camera.
It’s impressive that a consumer camera could stand up to professional cinema rigs, but there is a great degree of subjectivity at play here. The skill and decisions of each cinematographer definitely played a key role, as did the personal preferences of those voting.
My personal reaction after watching the blind comparison was that the GH2 shot had sort of a clinical, plastic feel to it. I most favored what turned out to be the RED Epic. But whatever you are drawn to, a test like this is an amazing testament to the capability of the tools available to today’s budding filmmakers.
One of the new iPad’s video features—along with 1080p recording and video stabilization—is temporal noise reduction. Apple claims it will improve the quality of footage in low-light conditions. OK, but what the hell is it?
It’s a clever technique…
There’s no getting around this: temporal noise reduction is tough to explain. That’s because it’s a complex process used to improve image and video rendering. This is very much a simplified explanation of what happens.
…that greatly reduces the noise of video…
When you record footage in low-light conditions, the resulting images are often noisy—speckled with pixelation that looks like a staticky TV screen. Why? Because there’s just not enough light hitting the sensor. In bright conditions, all the light provides a huge signal; noise—from electrical interference or imperfections in the detector—is still present, but it’s drowned out. In low light, the signals are much smaller which means that the noise is painfully apparent.
…by comparing what pixels actually move…
So, onto temporal noise reduction itself. Basically, it exploits the fact that with video there are two pools of data to use: each separate image, and the knowledge of how the frames change with time. Using that information, it’s possible to create an algorithm that can work out which pixels have changed between frames. But it’s also possible to work out which pixels are expected to change between frames. For instance, if a car’s moving from left to right in a frame, software can soon work out that pixels to the right should change dramatically.
…and guessing what is noise and what is actual detail…
By comparing what is expected to change between frames, and what actually does, it’s possible to make a very good educated guess as to which pixels are noisy and which aren’t. Then, the pixels that are deemed noisy can have a new value calculated for them based on their surrounding brothers.
…to make low-light video super-sharp.
So, the process manages to sneakily use data present in the video stream to attenuate the effects of noise and improve the image. It’s something that’s been used in 3D rendering for years, but it requires a fair amount of computational grunt. Clearly, the new iPad can handle that—and as a result, we’ll be fortunate enough to have better low-light video.
“Lilyhammer” tells the story of an East Coast mobster, played by “The Sopranos” actor Steven Van Zandt, who’s relocated to a small town in Norway as part of the witness protection program.
Unlike most TV shows, you’ll be able to see all eight episodes of “Lilyhammer” at once — Netflix is putting the whole series online February 6.
This seems to be a risky strategy: shows often build buzz over the course of the season, especially with a new series, and if “Lilyhammer” doesn’t catch on immediately it could have a hard time building viewership.
Netflix might be counting on a viral audience, with subscribers passing it between each other and telling their friends they need to see it. If that’s the case, it better be good.
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What looks like the card slot from a Chase Bank ATM is actually a sophisticated card skimmer removed from a branch in West Hills, California. And police believe a 3D printer may have been used to create it.
Those green bulbous card slots that were supposed to make it very difficult for a card skimmer to be attached to an ATM have turned out to be just a minor inconvenience for sophisticated thieves. Investigators believe this skimmer—which perfectly fits over the ATM’s regular slot— was created from a mould that came from a 3D printer. Which means those behind this particular ATM scheme had some very expensive tools at their disposal.
In addition to being a perfect replica of the ATM’s standard card slot, this skimmer incorporates a small pinhole camera that starts recording the PIN pad whenever a card is inserted. On the underside is a series of holes that investigators believe allowed the thieves to download data and footage, but the complex electronics on the inside may have been salvaged from a cellphone, giving this skimmer wireless connectivity. So in the future, like in many situations, make sure you take a good look at the hardware before you stick your thing in the slot. [KrebsonSecurity via BoingBoing]
Dr. Augustine Fou is Digital Consigliere to marketing executives, advising them on digital strategy and Unified Marketing(tm). Dr Fou has over 17 years of in-the-trenches, hands-on experience, which enables him to provide objective, in-depth assessments of their current marketing programs and recommendations for improving business impact and ROI using digital insights.
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