The widespread adoption of mobile electronic devices and the advent of wearable computing has encouraged the development of compact alternatives to the keyboard and mouse. These include one-handed keyboards, digitizing tablets, and glove-based devices. This paper describes a combination pointer position and non-chorded keystroke input device that relies on miniature wrist-worn wireless video cameras that track finger position. A Hidden Markov Model is used to correlate finger movements to keystrokes during a brief training phase, after which the user can type in the air or above a flat surface as if typing on a stan- dard keyboard. Language statistics are used to help dis- ambiguate keystrokes, allowing the assignment of multiple unique keys to each finger and obviating chorded input. In addition, the system can be trained to recognize certain fin- ger positions for switching between input modes; for exam- ple, from typing mode to pointer movement mode. In the latter mode of operation, the position of the mouse pointer is controlled by hand movement. The camera motion is es- timated by tracking environmental features and is used to control pointer position. This allows fast switching between keystroke mode and pointer control mode.