Automatic Object Modeling by Observing Human-Object Interaction

We propose a method for constructing object appearance models by observing human-object interaction in a household environment. Using this model, the system is able to perform object recognition by feature matching.

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Using Depth to Increase Robot Visual Attention Accuracy during Tutoring

We explore the problem of attention models for robot tutoring as related to the cognitive development of infants. We discuss the factors that have an important influence in the attention of infants and the way these factors can be taken into consideration to develop robot attention models that simulate infants’ cognitive stimuli.

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Robot Reinforcement Learning using Crowdsourced Rewards

This work is inspired by the idea that robots should possess the ability to learn new skills with minimum guidance from a dedicated human teacher and they should enhance their abilities by utilizing external resources such as the Internet.

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