Creating collar-sensed motion gestures for dog-human communication in service applications

Working dogs are dogs with one or more specific skills that enable them to perform essential tasks for humans. In this paper we examined motion gestures that working dogs could use to unambiguously communicate with their human companions. We analyzed these gestures in terms of true positives and propensity for false positives by comparing their dynamic time warping distances against a set of everyday gesture libraries (EGL) representing their daily movements. We found four gestures that could be concretely defined, trained, and recognized. These gestures were recognized with 75--100% accuracy, and their false positive rate averaged to less than one per hour.