Video monitoring, crowd surveillance, and detecting and identifying hard-to-see objects and anomalies in medical images are among the many tedious human tasks that can be performed or enhanced using computer vision technology with remarkable speed and accuracy – and it’s the kind of advanced technology being developed at the UCF Center for Research in Computer Vision.
Computer vision is a field within computer science that uses complex computational methods that enable computers to quickly recognize and analyze patterns, gestures, facial features and objects in photos, videos and other images.
The Center, known as CRCV, has earned significant success throughout 2020 – even with the challenges of a global pandemic – including winning a world championship in computer vision. CRCV faculty have published game-changing research and landed major research grants throughout the year that began with director Mubarak Shah’s induction into the National Academy of Inventors. Below is a summary of CRCV’s 2020 headlines and highlights.
UCF Team Wins Worldwide Competition in Computer Vision
Aug. 7, 2020 – UCF’s Center for Research in Computer Vision won a worldwide competition to improve computer vision by creating technology that can automatically track behavior in long security videos. The competition, called the Activities in Extended Video Challenge for 2020, was sponsored by the U.S. Department of Commerce’s National Institute of Standards and Technology and was held virtually in June as part of the Conference on Computer Vision and Pattern Recognition. Top computer vision teams from around the world, including teams from IBM, Massachusetts Institute of Technology, Carnegie Mellon University, and Purdue University competed in the challenge.
AI Can Detect COVID-19 in the Lungs Like a Virtual Physician, New Study Shows
Sept. 30, 2020 – CRCV researcher Ulas Bagci is part of a new study showing that artificial intelligence can be nearly as accurate as a physician in diagnosing COVID-19 in the lungs, and can distinguish COVID-19 cases from influenza. The study, recently published in Nature Communications, shows the new technique can also overcome some of the challenges of current testing. Researchers demonstrated that an AI algorithm could be trained to classify COVID-19 pneumonia in computed tomography (CT) scans with up to 90 percent accuracy, as well as correctly identify positive cases 84 percent of the time and negative cases 93 percent of the time.
UCF Lands $1 Million Grant to Advance Machine Learning-Vision Technology
Aug. 13, 2020 – Mubarak Shah, UCF Trustee Chair Professor, was recently awarded a $1 million grant to advance his cutting-edge work in the area of machine vision learning (artificial intelligence) and develop a system to thwart attacks on such systems. Shah, the director of UCF’s Center for Research in Computer Vision, and his team work on a variety of research-teaching machines to detect objects and classify them, and to track objects in video and analyze their behavior. The research and technology the center develops has applications in an array of areas critical to the nation from scanning crowd scenes to detect and prevent threats, to analyzing brain scans for tumors.
Bagci Awarded $4.56 Million in National Institutes of Health RO1 Funding
April 2020 – CRCV researcher Ulas Bagci, SAIC Professor in the UCF Department of Computer Science, landed a highly-competitive RO1 award from the National Institutes of Health for his research: “Radiologist-Centered Artificial Intelligence for Lung Cancer Screening and Diagnosis.” The $2.06 million award supports Bagci’s research creating novel artificial-intelligence algorithms that detect cancer in medical images to enhance the work of radiologists, which could lead to earlier disease detection. He also received more than $2.5 million in 2020 from NIH to develop similar work examining pancreatic tumors.
Bagci is an expert in developing AI to assist physicians, including using it to detect pancreatic and lung cancers in CT scans. His work developing this advanced technology was featured as a cover story of Mayo Clinic’s research magazine Discovery’s Edge in 2019.
In March 2020, Bagci was awarded $1.33 million from the Florida Department of Health to develop an explainable artificial intelligence tool for predicting radiation therapy outcome in lung cancer patients.
Computer Vision Pioneer Mubarak Shah Named Fellow of National Academy of Inventors
Feb. 6, 2020 – UCF’s renowned computer science researcher Mubarak Shah has been named Fellow of the National Academy of Inventors for his innovations in the field of computer vision. Shah, UCF Trustee Chair Professor of Computer Science and Director of the Center for Research in Computer Vision, was recognized for his significant technical contributions and inventions in computer vision.
“This is exciting time for computer vision research in particular, and artificial intelligence in general,” says Shah. “Due to deep neural network learning disruption, we are able to solve problems today we never thought we would be able to. Computer vision is being used in medical image diagnosis, self-driving cars, manufacturing, video surveillance for safety and security, biometrics, and more.”