Last month, researchers at the University of Central Florida presented a new facial recognition tool at the IEEE Computer Vision and Pattern Recognition conference in Columbus, Ohio.
While there is no shortage of facial recognition tools used by companies and governments the world over, this one is unique in that its aim is to unite or reunite children with their biological parents.
The university’s Center for Research in Computer Vision initially got to work by creating a database of more than 10,000 images of famous people–such as politicians and celebrities–and their children.
It works by using a specially designed algorithm that breaks the face down into sections, and using various facial parts as comparisons; they are then sorted according to which matches are the most likely.
Though software for this purpose already exists, this tool was anywhere from 3 to 10 percent better than those programs, and it naturally surpasses the recognition capabilities of humans, who base their decisions on appearance rather than the actual science of it. It also reaffirmed the fact that sons resemble their fathers more than their mothers, and daughters resemble their mothers more than their fathers.
Body language is a powerful thing, allowing us to gauge the tone and intention of a person, often without accompanying words. But is this a skill that is unique to humans, or are computers also capable of being intuitive?
To date, picking up on the subtext of a person’s movements is still not something machines can do, however, researchers at MIT and UC Irvine have developed an algorithm that can observe small actions in videos and string them together, piecing together an idea of what is occurring. Much like grammar helps create and connect ideas into complete thoughts, the algorithm is capable of not only analyzing what actions are taking place, but guessing what movements will come next.
There are a handful of ways that this technology would benefit humans. For example, if could help an athlete practicing his or her form and technique. Researchers also posit that it could be useful in a future where humans and robots are sharing the same workspace and doing similar tasks.
But with any technological advancement comes the question of cost–not money, but privacy. In this case, would the positives outweigh the negatives? In what ways can you envision this tool being helpful for your everyday tasks?
Engineers at the University of California, San Diego, are using Computer Vision as a means of sorting cells, and thus far have been able to do so at a rate of 38 times faster than before. This process of counting and sorting cells is known as flow cytometry.
The analysis of the cells helps to categorize them based on their size, shape, and structure, and also can distinguish if they are benign or malignant, information that could be useful for clinical studies and stem cell characterization.
While this type of research was occurring before, it’s a job that has traditionally taken a lot of time. But now, the use of a camera on a microscope can analyze information faster–cutting the time from between 0.4 and 10 seconds to observe and analyze a single frame down to between 11.94 and 151.7 milliseconds.
In what ways do you see this technology making advancements in the medical and clinical world? How else can you imagine it benefitting science?
Computer Vision is an interesting kind of technology in many ways, but perhaps one of the most notable things about it is how applicable it is and can be in our every day lives. And although it’s not necessarily a “new” field, it is something that is gaining popularity and recognition in the lives of “normal” people, meaning those who are not scientists, researchers, programmers, etc.
Using an HD camera, a special lighting system, and a laser scanner, the setup can count grapes as small as 4mm in diameter, and using algorithms, is able to use the number of grapes and convert that to an estimated harvest yield. And while the margin of error is 9.8 percent, in humans, it’s 30, demonstrating that the Computer Vision system is more efficient and possibly more cost-effective.
Most everyone can recall a time when doctors or nurses have needed to draw blood or give shots and had trouble finding the proper veins. A company in California is all too familiar with this scenario, and in an effort to make the process of drawing blood more efficient, has created Veebot.
Veebot is essentially a robot phlebotomist. Relying on infrared lighting, an infrared camera, image analysis software, and ultrasound technology, the robot is able to locate the best vein for taking blood. All of this is checked and double-checked in the span of a few seconds in order to ensure that the first needle prick is successful.
Currently, the Veebot has been correct in its identification about 83% of the time, which is better than the average of humans. Once it has reached a 90% success rate, the company hopes to use the machine in clinical trials.
To see how this machine works, watch the video below:
Roboray is the name of the robot, who relies on cameras, real-time 3D visual maps, and computer vision algorithms to move around, “remembering” where he has been before. This allows the robot to navigate autonomously, even when GPS information is not available. The technology used for Roboray also allows the robot to walk in a more human-like manner, with gravity helping him walk. This not only requires less energy, but gives the robot a more human-like appearance.
Would you consider purchasing a robot like Roboray? What kinds of tasks would you find the robot most helpful in assisting you with?
In an effort to help protect and conserve endangered species, scientists have been tracking and tagging them for years. However, there are some species that are either too large in population or too sensitive to tagging, and researchers have been working on another way to track them.
Now, thanks to SLOOP, a new computer vision software program from MIT, identifying animals has never been easier. A human sorting through 10,000 images would likely take years to properly identify animals, but this computer program cuts down the manpower and does things much quicker. Through the use of pattern-recognition algorithms, the program is able to match up stripes and spots on an animal and return 20 images that are likely matches, giving researchers a much smaller and more accurate pool to work with. Then the researchers turn to crowdsourcing, and with the aid of adept pattern-matchers, are able to narrow things down even more, resulting in 97% accuracy. This will allow researchers to spend more practical time in the field working on conversation efforts instead of wasting time in front of a computer screen.
For most people, getting a duplicate key made is not so difficult a process. Of course dealerships charge more for car keys, but regular keys to your house or office often only cost a couple dollars to have made at your local hardware store. However, a new company, Schloosl, is using computer vision to make copies of keys that not only work, but in some cases are superior to the originals.
Before computer vision, keys had been made from photographs before, but it was a precise and difficult art. However, cameras and computer vision of today have made it much easier. Of course, people may ask why it is any better than a hardware store copy, and that’s due to the precision.
Instead of using a blank key that is roughly the same and cutting a copy from an inferior version of a key, computer vision is able to analyze photos pinpoint the exact measurements so that spacing between teeth and deepness or shallowness of the teeth is more accurate, resulting in a better overall product.
What are your thoughts? Would a better key make a difference for you? For more on this, read the Shloosl blog.