Tracking body and hands for gesture recognition: NATOPS aircraft handling signals database

We present a unified framework for body and hand tracking, the output of which can be used for understanding simultaneously performed body-and-hand gestures. The framework uses a stereo camera to collect 3D images, and tracks body and hand together, combining various existing techniques to make tracking tasks efficient. In addition, we introduce a multi-signal gesture database: the NATOPS aircraft handling signals. Unlike previous gesture databases, this data requires knowledge about both body and hand in order to distinguish gestures. It is also focused on a clearly defined gesture vocabulary from a real-world scenario that has been refined over many years. The database includes 24 body-and-hand gestures, and provides both gesture video clips and the body and hand features we extracted

Multi-signal gesture recognition using temporal smoothing hidden conditional random fields

We present a new approach to multi-signal gesture recognition that attends to simultaneous body and hand movements. The system examines temporal sequences of dual-channel input signals obtained via statistical inference that indicate 3D body pose and hand pose. Learning gesture patterns from these signals can be quite challenging due to the existence of long-range temporal-dependencies and low signal-to-noise ratio (SNR). We incorporate a Gaussian temporal-smoothing kernel into the inference framework, capturing long-range temporal-dependencies and increasing the SNR efficiently. An extensive set of experiments was performed, allowing us to (1) show that combining body and hand signals significantly improves the recognition accuracy; (2) report on which features of body and hands are most informative; and (3) show that using a Gaussian temporal-smoothing significantly improves gesture recognition accuracy.United States. Office of Naval Research (Science of Autonomy program, Contract #N000140910625)National Science Foundation (U.S.) (NSF grant #IIS-1018055