Counting grapes with Computer Vision

Photo courtesy of Carnegie Mellon
Photo courtesy of Carnegie Mellon
It’s not secret that Computer Vision is an asset in the agricultural world, yet it’s still interesting to discover the new ways in which it is being put to you. For example, researchers at Carnegie Mellon University’s Robotics Institute published a study demonstrating how visual counting – one of the elementary Computer Vision concepts – is a way of estimating the yield of a crop of grapes.

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.

Computer Vision studies bird flocking behavior

Photo courtesy of Andreas Trepte.
Photo courtesy of Andreas Trepte.
Flocking is a behavior exhibited in birds, which is similar to how land animals join together in herds. And while there is an intricate pattern to this flocking, it’s difficult to establish exactly how birds communicate to keep this form. Their movements are synchronous, but the question is: how do birds on the outer edges of the flock stay in sync and help guide the group? Luckily, we have computer vision to help answer that question.

Before, scientists used to simulate this behavior and then compare it to what occurs with birds in real life in an attempt to demonstrate the how and the why. However, now computer vision can measure both position and velocity of objects in a frame, thanks to the work of William Bialek at Princeton University, which is demonstrating that birds are capable of matching the speed and direction of their neighbor birds.

Additionally, the concept of “critical point” helps explain this, showing that the social desires of the birds overwhelms the motivation of each individual bird, as they work toward flying as a collective flock and not as solo birds.

There still remains more to be seen and explored, but check out this study for further reading.

Meet the robot phlebotomist

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:

Computer Vision used in game analysis

Image courtesy of Disney Research
Image courtesy of Disney Research
Researchers at the Pittsburgh campus of Disney Research are using computer vision to analyze the patterns of field hockey players, in hopes of creating a new way for coachers and commentators to make sense of game data in real time. Furthermore, this technology can be used not only in field hockey, but any other kind of team sport with continuous play.

With a focus on player roles, the research zeroes in on the tactics, strategy, and style for players and their teams. Eight cameras recording high-definition video are used to record matches and data from these is analyzed against other matches. The compiled information can give insight into strengths and weaknesses of teams and solid strategies for how to better face their opponents.

Roboray: the next step toward human-like robots

Photo courtesy of University of Bristol and Samsung
Photo courtesy of University of Bristol and Samsung
Many people have imagined a day where robots would be advanced enough to help them with simple and complex tasks alike, and now researchers at the University of Bristol have joined forces with Samsung and taken steps toward accomplishing that.

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?

Computer Vision aids endangered species conservation efforts

Photo by Dr. Paddy Ryan/The National Heritage Collection
Photo by Dr. Paddy Ryan/The National Heritage Collection

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.

Computer Vision detects heart rate

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are now using computer vision to determine heart rate. Using an algorithm that analyzes small movements in the head, researchers are able to connect those movements to the rush of blood caused by the beating heart, in turn determining the heart rate. This opens doors for testing those who, for one reason or another, maybe not be the best candidates for EKG testing.

Copying keys with Computer Vision

Photo courtesy of Shloosl
Photo courtesy of Shloosl

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.

Computer Vision sees faces in the clouds

Image courtesy of Shinseungback Kimyonghun
Image courtesy of Shinseungback Kimyonghun

Computer Vision has many practical uses, ranging from security enhancement to making our lives easier, but what about art?

A new project, Shinseungback Kimyounghung, was launched by two South Koreans who are using Computer Vision to find faces in the clouds. This is similar to how children often lay on their backs and point out shapes in the sky, but instead, relies on computer algorithms to spot faces.

However, while the project appears artistic on surface level, examining it deeper reveals a study comparison how computers see versus how humans see. What the end result will be isn’t yet clear at this point, but it’s an interesting and thoughtful take on the subject nonetheless.