Android And Static Facial Recognition

Android and Static Facial Recognition practiced by team ACS lead by Dr. Lawrence Chung and collaborators Dr. Shinyoung Lim, Center of Rehabilitation, Univ. of Pittsburgh developed Hope. Hope would be a handheld application, preferably on smartphones that would assist people with communication disablity perform day-to-day activity. Day-to-day activities may include activities like having medicines at a particular time, going from home to nearby park and back, recognition of persons face to refresh memory about the relation both people share, etc.

Approach Mobile / Google

The concept was described as to carry out activities a healthy human being heavily depends on vocabulary. An ideal healthy person would have ability to talk, read, interpret/listen or write. Through the team’s project, the objectives would help people who need assistance with this senses through a handheld device. Static and Dynamic Face Detection is being implemented if the user taps its “Dynamic Detection button” after focusing on the image preview in camera. The user will then see a rectangle box in middle of the screen which will be moving as the face preview in camera changes position.

Face recognition still has its challenges. Ralph Gross, a researcher at the Carnegie Mellon Robotics Institute, describes one obstacle related to the viewing angle of the face as, "Face recognition has been getting pretty good at full frontal faces and 20 degrees off, but as soon as you go towards profile, there've been problems." Datasets are also a problem among facial recognition researchers.

Learning from new technologies like video face recognition is as effective. Adapting to such certification programs and interactive technologies serves just as important. As more video and facial recognition technologies emerge, the value of new skills and being an independent learner will increase just as effective as traditional methods.

Static facial recognition can further yield insights towards design, automation and synthesis framework. Static data is derived by its technologies such as Android. A photo can be systematically manipulated through variations required for experimentation yet at the same time being able to make the photo appear real. These manipulations are easier to perform when conducted statically using an Android platform.