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Entries in computer vision (53)

Monday
Aug052013

Computer Vision Meets American Sign Language 

For millions of people worldwide, sign language is their primary method of communicating with other people. And now, thanks to Microsoft Kinect, they'll also be able to 'talk' to computers.

Researchers from Microsoft Research Asia are collaborating with colleagues from the Institute of Computing Technology at the Chinese Academy of Sciences to explore how Kinect’s body-tracking abilities can be used to recognize sign language. Results have been encouraging in enabling people who use sign language as their primary language to interact more naturally with their computers, in much the same way that speech recognition does, according to the Microsoft Research blog. (To see the research in action, check out the video.)

Kinect's 3-D trajectory matching capabilitieshave made it possible to translate sign language into text or speech and to guide communications between a hearing person and a deaf or hard-of-hearing person by use of an avatar.

Guided by text input from a keyboard, the avatar can display the corresponding sign-language sentence. The deaf or hard-of-hearing person responds using sign language, and the system converts that answer into text.

...

“We believe that IT should be used to improve daily life for all persons,”  says Guobin Wu, a research program manager from Microsoft Research Asia. “While it is still a research project, we ultimately hope this work can provide a daily interaction tool to bridge the gap between the hearing and the deaf and hard of hearing in the near future.”

So far, the technology only supports American sign language, but it will be expanded in the future as research continues.

Monday
Jun102013

The Robot That Could Save Agriculture

Robots that make life easier are pretty awesome in their own right. But what about a robot that would transform agriculture as we know it, while saving our health and helping the environment? That beats the heck out of a robotic barista.

Blue River Technology, based in Mountain View, Calif., is working on development of a robot that could solve the No. 1 problem in agriculture: eliminating weeds. Sure, that sounds simple, but how do you safely eliminate weeds without adding herbicideas to food crops, genetically modifying the seeds or resorting to costly, time-consuming manual removal?

Using computer vision, of course! Blue River's robot combines computer vision with advanced spray technology; when it is pulled behind a tractor, it uses a camera to look down at the field below. The bot processes what it sees in mere milliseconds, enabling it to distinguish weeds from plants. Then, it sprays only the weeds with herbicide. What a welcomed change from the traditional method of spraying an entire field with herbicide and genetically modifying crops to resist herbicide.

Blue River's method could prove better for consumers' health, the environment and farmers' wallets -- which, in turn, could lead to more affordable produce. Blue River, which was founded in 2011, plans to deploys its first robotic weed-busters this year, on California lettuce crops.

Tuesday
May212013

Beyond Computer Vision: Robot Uses Arms, Location and More to Discover Objects

We're one step closer to full-functioning (and learning!) robots that help with everyday human tasks.

A robot can struggle to discover objects in its surroundings when it relies on computer vision alone. But by taking advantage of all of the information available to it—an object's location, size, shape and even whether it can be lifted—a robot can continually discover and refine its understanding of objects, say researchers at Carnegie Mellon University's Robotics Institute.

The Lifelong Robotic Object Discovery (LROD) process developed by the research team enabled a two-armed, mobile robot to use color video, a Kinect depth camera and non-visual information to discover more than 100 objects in a home-like laboratory, including items such as computer monitors, plants and food items.

Normally, the CMU researchers build digital models and images of objects and load them into the memory of the adorably-named HERB—the Home-Exploring Robot Butler—so the robot can recognize objects that it needs to manipulate. Virtually all roboticists do something similar to help their robots recognize objects. With the team's implementation of LROD, the robot now can discover these objects on its own.

With more time and experience, the robot gradually refines its models of the objects and begins to focus its attention on those that are most relevant to its goal—helping people accomplish tasks of daily living.

The robot's ability to discover objects on its own sometimes takes even the researchers by surprise,” said Siddhartha Srinivasa, associate professor of robotics and head of the Personal Robotics Lab, where HERB is being developed. In one case, some students left the remains of lunch—a pineapple and a bag of bagels—in the lab when they went home for the evening. The next morning, they returned to find that HERB had built digital models of both the pineapple and the bag and had figured out how it could pick up each one.

"We didn't even know that these objects existed, but HERB did," said Srinivasa, who jointly supervised the research with Martial Hebert, professor of robotics. "That was pretty fascinating."

Discovering and understanding objects in places filled with hundreds or thousands of things will be a crucial capability once robots begin working in the home and expanding their role in the workplace. Manually loading digital models of every object of possible relevance simply isn't feasible, Srinivasa said. "You can't expect Grandma to do all this," he added.

Check out Science Daily's full press release for more information.

Tuesday
Apr162013

Incredible: Fujitsu Creates 'Touchscreen' for the Real World 

Talk about a "next-generation" user interface. This one is straight out of movies like Iron Man -- and coming soon to a Best Buy near you?

Imagine an "interactive, touchscreen-like system using objects in the real world" -- a system that lets you manipulate the content of a book or flyer much like you would the content of your smartphone. Using image-processing technology coupled with an ordinary webcam and a commercial projector, Fujitsu has done just that.

So, the user can actually "cut and paste" from a hard copy document, placing the cut text or image or within a digital document, for example. Or, "link" to digital content while viewing a hard-copy document. The possibilities are far-reaching and super exciting. The best part? Fujitsu plans to bring a commercial version to market by the end of 2014.

Watch the video for full details of the system's capabilities.

Tuesday
Dec112012

Prism Skylabs Marries Loss Prevention, Customer Analytics

The line between security and customer analytics is becoming more and more blurry. And, according to an article on NRF's website, STORES.org, retailers are beginning to realize that for them, the two can be one in the same.

Case in point: Brown Shoe Co., which has partnered with Prism Skylabs to gain cutting-edge loss prevention technology and priceless customer analytics data for its Famous Footwear and Naturalizer stores.

The system combines next-generation video surveillance with detailed customer analysis, enabling stores to track the path that customers take through their stores, what merchandise they’ve touched, where and for how long.

“We can hire marketing companies that do this by sitting outside the store and observing. They count customers, look at linger time and where customers are going,” [vice president of asset and revenue management Jon] Grander says. “With Prism, we not only do this in real time but over an extended period of time. We can also watch thousands of customers across different platforms and gather some very interesting information to improve our store designs, promotions and what our sales associates are doing.”

As budget-conscious companies seek for ways to do more with less, technology like Prism Skylabs only makes sense. We expect to see more security-marketing convergence like this in the coming years.