Real-time vision-based human hand recognition has typically been focused on fingerprint recognition and palm print recognition for authentication applications. These conventional recognition methods process a small amount of hand feature data and usually execute on large, expensive computer systems in a non-real-time fashion. To recognize a human hand out of complex backgrounds, tracking hand movement and interpreting hand movements into predefined gesture identification have conventionally been limited by capabilities of imaging systems and image signal processing systems and typically involve a database for pattern matching, requiring a significant amount of computing power and storage.
Conventional human control system interfaces generally include human to computer interfaces, such as a keyboard, mouse, remote control and pointing devices. With these interfaces, people have to physically touch, move, hold, point, press, or click these interfaces to send control commands to computers connected to them.