Now the Ads Watch You

From Fox4kc.com:

Watch an advertisement on a video screen in a mall, health club, or grocery store and there's a growing chance the ad is watching you too. Small cameras can now be embedded in the screen or hidden around it to track who looks at the screen and for how long. The makers say the software can determine the viewer's gender, approximate age range, and, in some cases, ethnicity, and can change the ads accordingly.

Tru-Media , the makers of the technology, argue that its next generation advertising systems don’t have privacy implications in that they only enable ads to become more targeted. Actual images and identity information are not transmitted back to their servers; only general counts and other statistics relating to ad viewership are retained.

Still, I think that elderly shoppers might not welcome the idea of ad monitors suddenly switching to commercials for Boniva, Depends, and Quaker Oatmeal as they walk by.

Adobe Video-Object Manipulation Project Holds Significant Promise

Video Object Manipulation may be going mainstream.

Once the exclusive domain of computer vision geeks in the Department of Defense, and more recently Hollywood, Adobe has now got its hands on these algorithms and every YouTuber with an HD camera will soon have the tools to not only mark up video in fantastic new ways, but literally to bend reality.

What does it mean for security when just about anyone can add, remove or alter people and objects within a video stream to create a perfectly realistic video of something that never happened? Well, in my opinion it’s mostly not good.

But, there is a bright side -- the entrance of consumer-focused companies like Adobe into this industry is likely to help the security professionals as much as the criminals. More experts, new approaches, better tools and easier-to-use interfaces are a welcome addition to security’s video analytic offerings, and can certainly help security personnel fulfill the promise of improved surveillance.

Trace & Extract 3D Objects from Video

From Australian Centre fro Visual Technologies:

VideoTrace is a system for interactively generating realistic 3D models of objects from video—models that might be inserted into a video game, a simulation environment, or another video sequence. The user interacts with VideoTrace by tracing the shape of the object to be modelled over one or more frames of the video. By interpreting the sketch drawn by the user in light of 3D information obtained from computer vision techniques, a small number of simple 2D interactions can be used to generate a realistic 3D model. Each of the sketching operations in VideoTrace provides an intuitive and powerful means of modelling shape from video, and executes quickly enough to be used interactively. Immediate feedback allows the user to model rapidly those parts of the scene which are of interest and to the level of detail required. The combination of automated and manual reconstruction allows VideoTrace to model parts of the scene not visible, and to succeed in cases where purely automated approaches would fail.

Amazing Video Enhancement Technology

Researchers at the University of Washington recently released a video showing a series jaw-drapping video enhancements now possible using various image analytic and modeling techniques. In one demo of interest, simply by mixing a few high-resolution photographs of a scene with a lower quality video stream, the scientists were able to dramatically enhance the quality and resolution of the complete video...by 4x.

The technology could also be used to seemlessly remove private content from surveillance video, truely making proctected images of people or objects invisible. That's probably welcome news to some, but disconcerting to law enforcement professials who already have significant concerns about the reliablity of photos presented them. Video has been generally thought of as much harder to manipulate...no more.

Computer Vision Resarch Goes Virtual

Sometimes the real world just isn’t real enough. That’s often the case in computer vision application development where super smart PhDs seek to create algorithms and technologies to track and classify people or objects within a video stream. Believe it or not, some of the same neural networks that catch bad guys today got their start by tracking frantic scientists running around their labs, offices, and dorm rooms.

But ObjectVideo thinks there is a better way…at least to start. Using technology from the videogame Half Life 2 , they have built a Virtual Video Tool that can be used to create “virtual surveillance” cameras.

The ObjectVideo Virtual Video (OVVV) Tool generates realistic video from simulated cameras in an interactive virtual world. This tool is free and is based on a modification (aka 'mod') of Half-Life 2, a commercially available game from Valve Software. Our hope in distributing this tool is to stimulate computer vision research in areas that cannot rely on canned video (eg. active tracking) or when large quantities of ground truthed video is unavailable or impractical (multi-camera installations, public spaces, the list goes on!).

The fact that virtual cameras are generally thought to lack the video noise and other artifacts found in real-world cameras, doesn’t prevent this tool from providing real benefits to students and researchers. Today gaming engines are so realistic and of such high quality that the line between real and virtual is being blurred. And, as OV points out, virtual cameras provide another benefit that’s impossible to achieve with real world footage: ground truth data that can be incorporated into the training process. Because virtual cameras are built on models of scenes where ever person and object and color and angle are actually known, a researcher always knows, without guess or estimation, just how well their computer vision algorithms are deciphering a particular video stream.

Beyond that, ObjectVideo has created most of the environments, models, and camera option necessary to test every conceivable surveillance variation during the testing process. Even blur, noise, and even lens and PTZ effects can be simulated with relative ease.

Virtual surveillance video is not just a great tool for computer vision researchers, it’s also an incredibly interesting area of research in itself. The folks at Valve Software have my appreciation for opening their platform enough to enable this kind of work. But believe it or not, Valve’s Half Life 2 is already almost 4 years old. Maybe ObjectVideo’s next endeavor can be a Crysis mod. That would be something. And next year there will be something else…even better.

Hacking Face Rec

This is why we are constantly evolving our technology and developing new video algorithms. Granted, some people viewing this will follow the creator's advice, "Don't go out and rob a bank!" but there are probably a few who will attempt exactly that.



Invisible Mask - video powered by Metacafe

Surveillance as Handy Marketing Tool

A lot of new products are coming out that help companies use existing CCTV surveillance technology for marketing purposes--capturing everything from basic data about how many people stopped at a promotional display to more advanced details about particular customers. In addition to the camera-and-box equipped billboards being piloted by TruMedia and Quividi, Google recently announced its partnership with a company called Xuuk to produce a palm-sized camera called the Eyebox that will track how many times people look at both billboards and products in stores. The idea is to provide brick-and-mortar stores or companies the same tracking abilities in real life as they have with Google ads online. Personally, I think using face recognition with an already existent system (like, I don't know, a 3VR system!) makes better financial sense than spending $25,000 for a separate system and cameras, but even above and beyond that, using surveillance systems as marketing tools doesn't exactly help to assuage the public's "Big Brother" concerns about surveillance.

Half-moth Half-robot All-seeing

Researchers at the University of Arizona have accomplished the amazing, and somewhat bizarre, feat of connecting a 6-inch-tall wheeled robot to the brain of a moth. As the moth observes activity around it, the signals from its brain are translated and sent to a computer that directs the robot to turn toward wherever the moth is looking.

The moth's vision has evolved over millions of years to accurately guide the
insect as it dodges predators or seeks mates. Although the moth brain is
the size of a grain of rice, the insect's ability to detect motion is "amazing
-- beyond anything we could build," said senior author Charles M. Higgins, an
associate professor of electrical and computer engineering at the University of
Arizona.

The researchers also pointed to other potential uses for moth-based technology:

Higgins said a robot hooked into the moth's sophisticated olfactory system might
one day be used to detect bombs. After all, he said, "if it blows up, all you've
lost is a moth."

If it Walks Like a Terrorist

Behavior scientists at the University of Buffalo received an $800,000 grant to develop a technology that would help identify terrorists by their behavior. The project aims to fuse a variety of known biometric and video analysis technologies into a single “malfeasance score.”
“No single biometric is suited for all applications,” said Govindaraju, who also is founder and director of UB’s Center for Unified Biometrics and Sensors. “Here at CUBS, we take a unique approach to developing technologies that combine and ‘tune’ different biometrics to fit specific needs. In this project, we are focusing on how to analyze different behaviors and come up with a single malfeasance indicator.” The UB project is among the first to involve computer scientists and behavioral scientists working together to develop more accurate detection systems based on research from each field.

I wish them luck, but this is a tremendously difficult problem to solve.