Tag Archives: Recognition

Determining familial matches with Facial Recognition

Photo courtesy of UCF

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 Continue Reading

ComputerVision steps up soldiers’ game

Photo by Bill Jamieson

ComputerVision has long been of interest to and utilized by the United States government and armed forces, but now it appears as though the army is using this technology to help transform soldiers into expert marksmen. Tracking Point, a Texas-based startup that specializes in making precision-guided firearms, sold a number of “scope and trigger” kits Continue Reading

VISAPP Computer Vision conference extends submission deadline

VISAPP_2014_conference_logo

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 Continue Reading

Counting grapes with Computer Vision

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 – Continue Reading

Computer Vision aids endangered species conservation efforts

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 Continue Reading