A Robust Algorithm: Find an Unknown Person via Referring Grounding

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We propose a simple but robust method to recognize an unknown person described in natural language. In this case, a robot is given a verbal description about a person whom the robot is required to recognize. This task is challenging since humans and robots have significantly mismatched perceptual capabilities (e.g., recognizing the color of a coat). Without assuming that all linguistic descriptions and perceptual data are correct, we use a probabilistic model to ground the target person. In particular, the acceptability of color descriptions is modeled based on visual similarity and the confusion matrix of the color classi- fier which make the system more robust to illumination. Two groups of experiments were conducted. Our experimental results demonstrate that our system is robust to both perception and description errors.

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 address = {Nagoya, Japan},
 author = {Xiping Wang and Feng Wu and Dongcai Lu and Xiaoping Chen},
 booktitle = {Proceedings of the Robot World Cup XXI Symposium (RoboCup)},
 month = {July},
 title = {A Robust Algorithm: Find an Unknown Person via Referring Grounding},
 year = {2017}