Computer Vision Central's blog
Computer Vision Central publishes 1,000th news item
One thousand days ago Computer Vision Central started publishing a daily news item. In that short span of time -- less than three years -- the field has exploded. A look back through the news items we've published on this site proves that participation in computer vision encompasses all regions of the world; includes many types of actors -- individuals, academia, large companies, startups, governments, and non-profits; and benefits too many different industries to list. Computer vision has truly gone mainstream: it is embedded in our devices including smartphones, cars, and video game consoles; it is a topic of conversations in social networks; and it is regularly covered in mainstream news channels.
What's next? With so much happening in the computer vision world, and so much of it easy to find via social networks, a centralized limited-authorship computer vision news blog is less necessary today than it was 1,000 days ago. We will refocus the site on its most popular crowdsourced features: computer vision jobs, forums, and conferences. The computer vision jobs board will be the new front page. We will no longer post daily news, although all existing articles will continue to be available. If you see something in the computer vision world that excites you, we encourage you to share it with your fellow computer vision enthusiasts by posting about it in Computer Vision Central's forum!
Robotic automation coming to plant nurseries
Eric Smalley writes in a Wired report that several companies are testing autonomous robots for plant nurseries that grow ornamental shrubs and trees. The robots use computer vision and other sensors to navigate and to pick up and deliver potted shrubs and trees. One startup, Harvest Automation, has raised $5 million in venture capital. A video of the robots in action is available here.
Related articles on Computer Vision Central:
- Computer vision for agriculture increases profits, reduces waste
- Google awards research grant in mobile crop surveillance
- Computer Vision used to target individual weeds
- Vision-based pruning system reduces labor costs in vineyards
- Senate-approved Department of Agriculture appropriations bill includes funding for computer vision staff
- Vision analysis can estimate crop yields earlier
U.S. funds research towards street intersection analyzer for the blind
The U.S. National Institutes of Health (NIH) is providing $400,000 in funding to Dr. James Coughlan, of the Smith-Kettlewell Eye Research Institute, to develop tools to help the visually impaired. Building on the team's existing computer vision software for detecting crosswalks and 'walk' lights, the new system will help the blind and visually impaired navigate across intersections via continous feedback. The goal is to deploy the system in the form of free smartphone apps for common platforms such as Android and iOS so that users will not have to carry a separate device.
NVIDIA introduces Tegra 3 for tablets and phones
NVIDIA has introduced the quad-core Tegra 3 for mobile devices including tablets and phones. This embedded system was formely code-named "Project Kal-El". In addition to the four high-performance main cores, the Tegra 3 comes with a fifth low-power core which is used when high-performance applications are not running, to extend battery life. There is also a new 12-core GeFORCE GPU. The Tegra 3 will provide a powerful new platform for mobile computer vision applications.
Related articles:
Tracking all the players on the field
A team of researchers from Switzerland's Ecole Polytechnique Fédérale de Lausanne (EPFL) have developed a system that can continously track every player on the field in a sporting event, even through occlusion events. The system is entirely based on eight cameras positioned around the field, and does not require the players to wear any devices. The research was presented at ICCV 2011 this week. More information is available in a press release.
Students win competition with Kinect visual gait analysis
In the recent Siemens Competition in Math, Science and Technology held at Georgia Tech, high school seniors Ziyuan Liu and Cassee Cain took first place in the regional championship. Their project used the Xbox Kinect and computer vision to analyze human gait. The Oak Ridge High School seniors will advance to the national competition on Dec. 2-5 in Washington D.C., where they will compete for a $100,000 scholarship. More information is available in a Knoxnews article.
New MIT algorithm speeds up MRI scans
Researchers from MIT (Elfar Adalsteinsson and Vivek Goyal) have developed a new imaging algorithm that could reduce magnetic resonance imaging (MRI) scans from 45 to 15 minutes. Using information from the MRI's first contrast scan, the algorithm predicts the likely object boundaries between different types of tissues in subsequent scans. The researchers are now working to improve the algorithm and accelerate the processing time on a GPU. More information is available in a MIT news article.
Improving smartphone cameras
The U.S. National Science Foundation (NSF) has awarded $450,000 to Colorado-based company FiveFocal to improve the manufacturing of camera modules for mobile phones and other platforms. The grant is primarily targeted to increasing yields, which would reduce costs; however, it is likely that the improved manufacturing process monitoring will lead to higher quality as well. Increasing numbers of apps that require computer vision software are being written for smartphone platforms; higher and more consistent imaging quality will enhance the performance of many of those computer vision apps. A detailed description of the project is included below.
Stanford Decaptcha identifies CAPTCHA weaknesses
Researchers at Stanford University have developed a tool to automatically decipher and defeat CAPTCHAs (Completely Automated Public Turing tests to tell Computers and Humans Apart). The research team (Elie Bursztein, Matthieu Martin, and John C. Mitchel) developed "Decaptcha" using various methods of cleaning up intentional background noise and breaking text strings into individual characters for easier recognition. They ran against CAPTCHAs used by 15 high-profile Web sites, and the only tested site that could not be broken was Google. Several recommendations to improve CAPTCHA security were provided, which include randomizing the length of the text string, randomizing the character size, applying a wave-like effect to the output, and using a collapsing background with lines. More information is available in a Network World article.
Related articles:
Apple buys C3 Technologies
According to GPS Business News, Apple is buying C3 Technologies for $267 million. C3 Technologies is a Swedish company that provides 3D images of cities. It has vision technology to create 3D models from oblique camera systems without LIDAR.