Computer-vision-based methods provide one general approach for obstacle detection and range estimation for pilot assistance during low-altitude flight. Results obtained using helicopter flight data with a feature-based range estimation algorithm are presented. A method for recursively estimating range using a Kalman filter with a monocular sequence of images and knowledge of the camera's motion is described. The helicopter flight experiment and one of four resulting datasets are briefly discussed. The performance of the range estimation algorithm is examined by comparing the range estimates with true range measurements collected during the flight experiment.>

An approach to securing access to computer systems is described. By performing real-time measurements of the time durations between the keystrokes when a password is entered and using pattern-recognition algorithms, three online recognition systems were devised and tested. Two types of passwords were considered: phrases and individual names. A fixed phrase was used in the identification system. Individual names were used as a password in the verification system and in the overall recognition system. All three systems were tested and evaluated. The identification system used 10 volunteers and gave an indecision error of 1.2%. The verification system used 26 volunteers and gave an error of 8.1% in rejecting valid users and an error of 2.8% in accepting invalid users. The overall recognition system used 32 volunteers and gave an error of 3.1% in rejecting valid users and an error of 0.5% in accepting invalid users.>