Dr. James Shackleford received an NSF CAREER award for his project "Low Latency, Parallel, and Context Aware Vision in Computed Tomography." In this five-year project, he will be developing a computational framework that enables rapid automatic identification of anatomical structure, deformation, and motion within the human body by employing new computer vision algorithms for MRI and CAT scans. In addition, Dr. Shackleford is developing innovative computer vision curricula as part of his CAREER plan in order to engage the graduate and undergraduate student populations in this exciting interdisciplinary field.
Digital images and videos can easily be altered using software such as Adobe Photoshop, then redistributed over the Internet. In response to this, researchers such as Dr. Stamm have developed a new class of security techniques known as "multimedia forensics." These techniques are capable of determining where an image or video originated, and if it has been altered or falsified. The research conducted under Dr. Stamm's NSF CAREER Award is aimed at addressing these problems by designing multimedia forensic algorithms capable of: (1) operating in "big data" environments, (2) exposing complex forgeries, and (3) responding to adversarial attackers attempting to fool forensic algorithms.
Most existing multimedia forensics research has focused on addressing basic questions such as "Did camera A take this image?" or "Was this image manipulated using editing operation B?" Little research, however, has focused on developing algorithms capable of quickly forensically analyzing large amounts of image and video data. Furthermore, there is a need for algorithms capable of uncovering sophisticated forgeries made by information attackers attempting to mislead multimedia forensic algorithms.
Please join the department in congratulating Dr. Shackleford and Dr. Stamm on their accomplishments.