Key frame extraction from video sequences containing ASL signs with concealed transmission errors

Most of the information processed by human brain comes from visual sources. That is why visual information is very important in human communication and decision making process. It is even more important for people whose other senses are negatively impaired. There are many people all over the world who rely on sign language to communicate with others. One of these languages is the American Sign Language (ASL). Many systems and algorithms that attempt to translate this communication into text with various success rates have been developed, but these systems cannot analyze each frame of video sequence in its full size. That is why an algorithm capable of tracking the gesturing hand and identifies key frames containing entire signs is highly desirable and important. Even more so considering how much are video channels, especially wireless video channels, susceptible to disturbances and noise.