K. P. Tee, R. Yan, Y. Chua, Z. Huang and S. Liemhetcharat, "Gesture-based attention direction for a telepresence robot: Design and experimental study," 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, 2014, pp. 4090-4095. doi: 10.1109/IROS.2014.6943138
Abstract:
The application of robotics to telepresence can enhance user interaction experience by providing embodiment, engaging behaviors, automatic control, and human perception. This paper presents a new telepresence robot with gesture-based attention direction to orient the robot towards attention targets according to human deictic gestures. Gesture-based attention direction is realized by combining Localist Attractor Network (LAN) and Short-Term Memory (STM).We also propose audio-visual fusion based on context-dependent prioritization among the 3 types of audio-visual cues (gesture, speech source location, head location). Experiment results are very promising and show that i) the average gesture recognition rate is 92%, i) gesture-based attention direction rate is 90%, and that ii) only by considering the 3 types of audio-visual cues together can the robot perform on par with a human in directing attention to the correct person in a meeting scenario.
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