Segways Used For Sniper Practice

Marathon Robotics and the Australian Defense Force teamed up to bring realism and a little fun to snipers in training. They outfitted Segways with foam bodies in hoodies for live-fire sniper training.

With the Rover system, there is no joystick -- the Segways are pre-programmed to follow a planned scenario. When a target is shot, it provides instant visual feedback by stopping and dropping its mannequin, and sends a message to other Segways to scatter.


Now, if only someone could program them to dance to "Thriller"!

DARPA To Build Star Wars' AT-AT-like Walkers

The Defense Advanced Research Projects Agency's Legged Squad Support System (LS3) program is a joint effort between DARPA’s Tactical Technology Office and the U.S. Marine Corps Warfighting Lab.

The program's goal is to develop a walking quadruped platform to help carry equipment autonomously. These platforms will be capable of managing rugged and complex terrain, where tactical vehicles are not able to go -- lightening the load of Marines and soldiers, and increasing their combat capability.

LS3 will carry 400 pounds or more of payload, and provide 24 hours of self-sustained capability over 20 miles. LS3 will weigh no more than 1,250 pounds (including its base weight, fuel and payload of 400 pounds).

Key LS3 program themes are:

(i)
Quadruped platform development: design of a deployable walking platform with sufficient payload capacity, range, endurance, and low noise signature for dismounted squad support, while keeping weight and volume scaled to the squad level.

(ii)
Walking control: develop control techniques that allow walking, trotting, and running/ bounding and capabilities to jump obstacles, cross ditches, recover from disturbances, and other discrete mobility features.

(iii)
User Interface (to include perception technologies): the ability for the vehicle to perceive and traverse its immediate terrain environment autonomously with simple methods of Marine/Soldier control.

Tiny, Paper-thin Camera and Iris Recognition Technology Being Field Tested for Military, Homeland Security

New miniature camera technology -- with the thickness of two stacked credit cards -- that can track the enemy in dark caves and urban alleys, and identify a person from an iris scan, is being field-tested for military and security uses.

Panoptes is an ultra-slim smart camera that combines images from low-resolution imagers to create a high-resolution image. The large number of tiny imagers are directed independently by a MEMS-controlled micro-mirror. Because there is no protruding lens, Pantoptes can be made flat.

A central processor combines the images into a single picture, producing a higher resolution than the individual imagers. The intelligent system can identify areas of interest -- for example, a face -- and concentrates the sub-imagers on only the area of interest -- the iris.

As Marc Christensen, project team leader at Southern Methodist University, explained, “After a first frame or two was collected, the system could identify that certain areas, like the open field, had nothing of interest, whereas other areas, like the license plate of a car parked outside or peering in the windows, had details that were not sufficiently resolved. In the next frame, subimagers that had been interrogating the field would be steered to aid in the imaging of the license plate and windows, thereby extracting the additional information.”

The resulting image is produced without "noise," and frame rates of 30 to 60 per second can be achieved using a normal digital signal processor.

Applications for this technology include military, border patrol and airports.

The new applications may be ready for demonstrations as soon as late 2011, said Christensen.

Mini Surveillance Airplane Mimics Bird Movements

RoboSwift is a micro airplane that is modeled after a common bird. It carries a mini-camera for discreet surveillance and sends footage wirelessly to a remote monitor. The airplane’s “feathers” fold backwards and its tail planes are transparent, creating a surprisingly lifelike effect.


RoboSwift was designed by a student team from the Netherlands as part of a competition to create innovative unmanned micro-aerial and ground vehicles.

Voice Recognition Technology Slowly Advancing

The problem with using voice recognition as a biometric is its slow processing speed.

However, researchers at North Carolina State University are attempting to
improve the speed of speech authentication, without sacrificing accuracy.

According to the research paper, “Joint Frame and Gaussian Selection for Text Independent Speaker Verification,” the research is based on Gaussian selection, a technique applied in the GMM-UBM framework to accelerate score calculation. The researchers modified the method known as sorted GMM (SGMM). SGMM uses scalar-indexing of the universal background model mean vectors to achieve fast search of the top-scoring Gaussians. They extended this method by using 2-D indexing, which leads to simultaneous frame and Gaussian selection. The results on the NIST 2002 speaker recognition evaluation corpus indicate that both the 1- and 2-D SGMMs outperform frame decimation and temporal tracking of top-scoring Gaussians by a wide margin.

Voice recognition technology can be used to prevent ID theft and data protection for the government, financial, healthcare and telecommunications sectors.

Simon the Robot Can Recognize Voices and Faces

Simon the Robot, developed by the Georgia Institute of Technology's Socially Intelligent Machines Lab in an effort to study human-robot interactions, showed off his learning abilities at the Computer Human Interaction conference in Atlanta this week.

With his computer vision, ability to respond to questions, identify items and match colors, voice recognition, facial recognition -- thanks to faceAPI from Seeing Machines -- and sound localization, Andrea Thomaz, Simon's creator, hopes Simon will be able to operate successfully in the real world one day.

At the conference, a researcher asked Simon, "Simon, can you hear me?" Simon responded "Yes." The researcher then asked him if he wanted to learn something and Simon reached out his robotic arm, grabbed the object -- a blue book -- and brought it to his face. He was told to put the book in the blue bin, and Simon dropped the book in the bin and said, "There you go."

The researchers' goal is for Simon to learn to do things on his own, without being programmed or prompted every time.

So, watch out, lazy husbands out there!

PhotoSpeak Breathes Life into Still Photos

MotionPortrait’s amazing PhotoSpeak 2.0 takes iPhone apps to the next level. The image-processing technology turns photos into “living, breathing” 3-D movies on your iPhone screen.

Interact with your “avatar” by prodding the screen with your finger—you’ll see your image blink and move—or make it speak by recording your own voice. The Visual Voicemail feature lets you send avatar messages to friends. Users can even manipulate celebrity photos and cartoon characters to create parrot-like avatars—because who hasn’t wondered what it would be like to see the Mona Lisa speaking Japanese?

Facial Recognition Called on to End Chatroulette’s Pervert Problem

Since Chatroulette's inception, the site's notorious genital-flashers have been driving off advertisers and normal folks more than the founders would like to admit. But now, thanks to a Business Insider contest called “Solve Chatroulette's Penis Problem and Help It Make Billions and Billions,” facial recognition may be coming to the rescue.

The contest winner, John Spyers, a senior project manager from Missouri, explains:

"Not one of the people I've encountered displaying their wares on Chatroulette shows their face. So, utilize a facial recognition scan or brief eye tracking scan before making connections. If there's no facial recognition, then pixilate [the] image and prompt to accept cam feed."

Why not go the other way and do penis recognition? The technology would be too easily fooled by a banana or other phallic object, Spyders said. And apparently a lot of people eat bananas on Chatroulette.

Smartphones That Can Save Your Life

My iPhone has changed the way I navigate through life, but it -- by itself -- can't save my life...yet.

Homeland Security's Science and Technology Directorate's Cell-All is an initiative that aims to equip cell phones with life-saving capabilities; for example, protecting against toxic chemicals.

The design would include a VOC sensor that will intermittenly test air samples to detect and identify toxic chemicals and automatically send an alert to the cell phone user via text, call or chime, as well as to a central station with the time, location and the compound.

Detection, identification and notification all take place in less than 60 seconds. And when a central station is flooded with alerts, false alarms are eliminated, enabling first responders to react faster.

As for privacy issues, Cell-All will operate only on an opt-in basis and will transmit data anonymously.
Forty prototypes that can detect carbon monoxide and fires are expected in about a year.

Computer Vision App Keeps Emoticons Honest

Auto Smiley is computer vision software that detects when you smile into your webcam, and then sends a corresponding smiley face to your computer. The emoticon will pop up in the front-most application, such as a chat window. The app promises to flood your chats with even more unnecessary emoticons; let’s hope LOL and ROFL computer vision isn’t next.

Software Identifies People By Shape of Noses

First there was fingerprint scans, then came retinal scans and soon, we might have nose scans?

Scientists from the University of the West of England and University of Bath claim scanning noses could be a quicker and easier way to verify a person's identity.

PhotoFace developed at UWE's Machine Vision Laboratory, takes several flash photos of a nose from different angles, in order to cast shadows around the nose.

Computer software creates 3-D images of the nose and categorizes the images based on six nose shapes: Roman, Greek, Nubian, Hawk, Snub and Turn-up.

The software then determines the color, surface orientation and depth of each point on the face by analyzing the shadows, a technique called photometric stereo.

Based on the measurements of the ridge profile, the nose tip, and the nasion or section between the eyes at the top of the nose, the researchers found that nose scanning showed good potential for use as a biometric, with a good recognition rate and a faster processing time than conventional biometric techniques.

The researchers will tweak the software to see if it can pick out individuals from a larger group of people, or distinguish between blood relatives.

Chicago’s Surveillance System Raises Privacy Concerns … Again

It’s official: No other U.S. city has such an extensive and sophisticated video surveillance system as Chicago. According to CBS News, the network of an estimated 10,000 cameras also includes innumerable private cameras and may grow to encompass tiny “covert” cameras in the future:

While critics decry the network as the biggest of Big Brother invasions of privacy, most Chicago residents accept them as a fact of life in a city that has always had a powerful local government and police force. Chicago police point to 4,000 arrests made since 2006 with the help of cameras. And, [a recent study] found crime in one neighborhood—including drug sales, robberies and weapons offenses—decreased significantly after cameras were installed.

Regardless of what the critics say, municipal surveillance is here to stay and will only become more prevalent, as even more cities begin to use cameras for everything from capturing and prosecuting criminals and exonerating the innocent to detecting parking violations. Privacy will continue to be an issue only because most surveillance systems are ineffective, even in Chicago, and certainly not private.

Despite how far surveillance has come, many cities still use technology from the 1980s. At the center of these archaic systems are giant video walls that require far too many employees to monitor. A network of 10,000 cameras may sound impressive, but pinpointing a certain event within that amount of data is nearly impossible without the right intelligent technology. This gap in turn creates an all-or-nothing situation in terms of privacy. The cameras and software can’t narrow in on a particular person, so review requires an overly wide net and involves too many innocent people.

There’s no denying that the world needs both security and privacy; the trick is to find a balance between the two. With so many current surveillance systems falling back on dumb cameras—and requiring an army of people to watch them—we get neither. The only way to bridge the security-privacy gap is with new technologies that enhance monitoring and visualization capabilities. Intelligent search allows officials to focus on particular people and make use of privacy protections like access control, encryption and face blurring.

Once we move past '80 technology, it's not only possibly to balance security and privacy concerns; more than that, we can actually acheive both.

Computer Vision Technology Propels Augmented Reality Forward

Imagine being able to access information about something just by looking at it.

The Telecommunications Research Center in Vienna has successfully demonstated the ability to do just that at an augmented reality conference in the French Alps. They linked a state-of-the-art eye tracker designed for Web analysis to a camera trained on a user's eye, another camera facing the user's scene and a smart phone with compass and GPS capabilities. Senors also were incorporated to follow the movement of the eye. Everything is attached to a bike helmet.

The smartphone tracks the user's orientation and location, and the sensors can determine that the user is looking at, say a building, a bridge or a monument. When the user closes his/her eyes for two seconds, it triggers a request for information about whatever was just in view.

A remotely accessed computer scans geo-referenced information on the Internet, such as Google Earth, and then forwards the result back to the user's cell phone in text-to-speech format.

The technology holds promise for all industries, especially military, security and retail.

A research team at the University of Tokyo also has adapted eye-tracking technology to be used as a memory aide.

Rather than training a camera on the eye, the "Aided Eye" system uses tiny infrared sensors mounted on a pair of eyeglasses.

The scope of this technology is more limited because instead of gathering information from the Internet, the team uses their own database of images and files.

In their experiment, the team entered 100 images into the database. When the eye affixed to an object, the computer was able to recognize the object and find it in the database. The team is still working out how to forward the information to the user -- a screen embedded inside the glasses' lens or an audio system are both options.

Camouflage Makeup Seeks to Foil Face-detection Technology

Can simple camouflage techniques undo the work of face-detection surveillance cameras? Adam Harvey, a designer and technologist with NYU’s Interactive Telecommunications Program, thinks so.

According to Popular Science, after reverse-engineering the algorithms behind face detection, Harvey created a series of blocky images that he says could be the “building blocks of anti-surveillance makeup.” Harvey has found that the most successful patterns are smaller than you might guess: A few random patches of makeup scattered around the eye seem to confuse face-detection software more effectively than larger patterns.

For those of you who are spooked by advancements like the facial recognition software iPhone app, Harvey’s research might lead to an easy—yet potentially off-putting—fix.

World's Largest DVR

The Godzilla of DVRs is here, sending millions of people fleeing -- to their TVs.

SnapStream's monster DVR system can record a whopping 50 channels at once. This requires the storage capacity of more than 125 TB (equivalent to 326 TiVo Premier boxes). As the name suggests, don't expect this device to fit comfortably into your entertainment system -- you'll need a 25U half rack!

Though all you need is a coax cable to hook it up, it does need two 15 amp power plugs and a 10 GB Ethernet (or up to 8 bonded 1GB ports) uplink.

The secret behind this technology is the clustering technology.

One SnapStream node is designated as the master and another can be designated to perform other functions. The “master” node doles out work to the various nodes. The network meshes the nodes together, allowing them to talk to each another, correctly balance workload and use each others' storage. The interconnect on this SnapStream Cluster is via an HP Procurve 2910 switch, with two 1 GB copper Ethernet ports bonded via LACP per server.

With the grand unveiling taking place at the National Association of Broadcasters Show in Las Vegas next week, it appears SnapStream is targeting the broadcasting/media market for now, but this capability will undoubtedly have the security industry chomping at the bit.

Get Ready for 3-D

(photo credit: The Boeing Co.)

We are on the cusp of the 3-D revolution.

3-D televisions are here. Panasonic and Samsung have launched their first 3-D TV sets, which allows consumers -- with included 3-D glasses -- to watch 3-D movies at home.

LG Electronics and Sony also will release their 3-D models by summer.

Sharp Corp. annouced plans to start making advanced 3-D displays for cell phones and other mobile devices that don't require special glasses.

Nintendo will launch the 3DS handheld game console that allows users to play 3-D games without using special glasses.

As for the security market, 3-D imaging for defense applications is gaining momentum.

The Boeing Co. offers a new, compact, energy-efficient camera that provides 3-D images for military and commercial applications.

The cube-shaped camera employs advanced sensors developed by the Massachusetts Institute of Technology's Lincoln Laboratory and is 1/3 the size and uses 1/10 the power of most comparable 3-D imaging cameras.

The camera can map terrain, track targets and see through foliage.

To create 3-D images, the camera fires a short pulse of laser light, then measures the pulse's flight time to determine how far away each part of the camera's field of view is.

The company plans to incorporate 3-D video capability to the camera.

Fuji and Sony also have begun marketing 3-D cameras and imaging systems.

Megapixel Cameras Used as Bionic Eyes

Researchers at Bionic Vision Australia have developed a bionic eye prototype called the wide-view neurostimulator that aims to restore vision for patients suffering from degenerative vision loss.

The “eye” is actually a 5 megapixel camera mounted on a pair of glasses. An electrode is implanted in the patient’s eye that connects to the retina. Vision-processing software in an external device wirelessly generates electrical impulses to create images.

The resulting image is a pixelated version of what a human eye would see – think Lite-Brite circa 1970s. The team is already working on a second-generation “eye” with 10x the resolution.

This technology holds great promise for the future of eye care.

Cell Phone App Raises Privacy Concerns

Although Recognizr, a new cell phone app, is still just a prototype, it’s already earning criticism for potential privacy concerns. Here’s how it works: You point your iPhone at someone, take a photo and click “Recognize.” The facial recognition software analyzes the image and identifies the person based on social media sites, such as Facebook and Twitter. It then links the image with their other information, like phone numbers and e-mail addresses.


Here’s a video of the prototype at work:





These days it seems like anything linked to the words “facial recognition” immediately raises privacy concerns. But apparently Recognizr requires a fairly stationary, head-on image to successfully identify someone, so it’s doubtful that you’re going to get “recognized” without your permission. Also, it’s unclear whether the photographer has to be friends with the subject on Facebook or MySpace for the app to access his or her information.

What Not to Wear...To the Airport

In commemoration of Easter, check out the FAA's version of "Easter eggs." My favorite has got to be the snakes, if only for the obvious "Snakes on a Plane" jokes!

Remote-controlled Helicopter Makes First Arrest

Flying remote-controlled helicopters have come a long way from crashing into lamps and ceilings in your mom's living room; today most 8 year olds have RC contraptions capable of video and nerf combat, at the very least.

Law enforcement also has some decent equipment these days. The Merseyside police in the U.K. just arrested a suspected car thief in January using a remote-controlled helicopter dubbed the Air Robot. Using the onboard thermal-imaging camera, the operator was able to locate the suspect, a 16-year-old male, in thick fog, hiding in bushes.

The £40,000 battery-powered silent-hovering drone can fly up to 500 feet high and has a range of 1,500 feet. It measures 3 feet long and can mount a variety of cameras, including CCTV, night-vision and thermal.

The Merseyside police have been using the drones in search and rescue operations and executing drug warrants for the past two years, but this is the first arrest that is attributed to the Air Robot.

It will be interesting to see if the evidence gathered from the drone will be accepted in a British court.

Female Androids Come to Life

Japanese roboticist Hiroshi Ishiguro, who is famous for creating a robotic duplicate of himself a few years ago, is back to creeping out the entire world, this time with a female android. Geminoid F, as she’s called, can smile, laugh and even display “emotions.” As you’ll see in the video, it’s sometimes hard to distinguish between the robot and the woman she was modeled after.






From IEEE Spectrum:

Geminoid HI-1 [is] designed to be remote controlled by an operator. In a press conference in Osaka, Ishiguro demonstrated how the android could mimic the facial expressions of the woman as she sat in front of a computer with cameras and face-tracking software.

[The team] wanted to create an android that could exhibit a wide range of natural expressions. … In particular, they wanted the robot to sport a convincing smile.

Facial recognition software used to make more humanlike robots? Fantastic. But the end result still looks like an invader from from the uncanny valley.