There You Go! - Estimating Pointing Gestures In Monocular Images For Mobile Robot Instruction

Abstract

In this paper, we present a neural architecture that is capable of estimating a target point from a pointing gesture, thus enabling a user to command a mobile robot to a specific position in his local surroundings by means of pointing. In this context, we were especially interested to determine whether it is possible to implement a target point estimator using only monocular images of low-cost Webcams. The feature extraction is also quite straightforward: We use a gabor jet to extract the feature vector from the normalized camera images; and a cascade of multi layer perceptron (MLP) classifiers as estimator. The system was implemented and tested on our mobile robotic assistant HOROS. The results indicate that it is in fact possible to realize a pointing estimator using monocular image data, but further efforts are necessary to improve the accuracy and robustness of our approach