Ogris - Ultrasonic and Manipulative Gestures

Ogris, Georg, et al. "Using ultrasonic hand tracking to augment motion analysis based recognition of manipulative gestures." ISWC 2005.

Summary

Wants to augment vision-based system with ultrasonic positioning system to determine what action is being performed on what tool/object in a workshop or something similar. They look at using model-based classification (series of data frames in sequence) with left-right HMMs. They look at frame-based classification using decision trees (C4.5) and kNN. They also examine methods of combining ultrasonic data to constrain the plausible classification results of the classifiers. They classify and get a ranked list, then pick the one that is most plausible given the ultrasonic data. If none are probably enough, ultrasonic data is said to be bad and most likely result of classification is chosen.

Using ultrasound alone we get 59% with C45 and 60% with kNN. We get 84% accuracy classifying frames of data with kNN. HMMs only perform with 65% accuracy, due to a lack of training data and longer, unstructured gestures. Using plausibility analysis, we can increase frame-based accuracy to 90%.

Discussion

I like that they use ultrasonics to get position data to help improve classification accuracy. But this doesn't seem like a groundbreaking addition. They just use a bunch of different classifiers and, gasp, find that contextual information (ultrasonic data) can improve classification accuracy.

Decent, but nothing ground breaking or surprising.