Modelling of Hand Gestures and Motions

Abstract: Measuring the radar response has proven to be a valid input for neural networks used for gesture and motion recognition. Previous work have been based on measuring the radar response of hand gestures, but it has been shown that models based on the analytic expressions for basic objects are useful when simulating larger motions, such as pedestrians. This work explores if a hand model made of basic objects can reach the same results as actual hands. To do this, this basic objects model is implemented in two different solvers to compare the difference in value and run-time between analytic expressions and Finite Element Method solutions. The Finite Element solution is shown to change value based on the simulated gesture, but the analytic model is proving to be far faster. In the end, the latter is not capable of reproducing the response of all motions which have been measured. Implementing object interaction into the analytic model should give this model the details required to simulate even the smaller gestures. Therefore, this model is still work in progress.