Arm Gesture Classification for Human-Robot Interaction -- Pattern Recognition Dataset
In the Robotic Life Group, we have a Vicon Motion Capture system. We will be offering a dataset of arm gestures for use in classification problems. The application of these gestures is for a mixed reality communication/interaction with an on-screen animated robot character (shown the figure). If you decide to work on this problem we'll have you come to the lab and see exactly how the data was collected to better understand the dataset you're working with.
The data set has 15 classes of gestures (3 gestures at 5 locations). Each gesture is a sequence of data captured from the Vicon system from a person wearing several markers on their right arm. We have two kinds of features from the Vicon markers, one is the raw marker positions (x,y,z) and the other is higher level skeletal information (e.g., wrist, elbow, ...) Ideally we would like to classify gestures with only the raw markers, but it is a much more challenging problem because there is no correspondence between the raw points from one frame to the next. In order to classify based on just the raw points, it might be necessary to derive higher level features (moments) from the bag of data points in each frame.