Predicting driver operations inside vehicles

In this paper, we propose a method for predicting typical operations performed by vehicle drivers such as ldquopushing a navigation buttonrdquo, ldquoadjusting the rear-view mirrorrdquo, or ldquoopening the console boxrdquo, before the driver actually reaches the target position. The prediction method uses the image position of anatomical landmarks (shoulders, elbows, and wrists) as they move over time. The difference of configurations among operations is modeled by a combination of clustering and discriminant analysis. The proposed method was applied to predict nine frequently executed operations inside a vehicle, running at over 150 frames per second. For five subjects, the method achieved an average prediction accuracy of 90% with a false positive rate of 1.4% at half the operation duration.