Enabling Depth-Driven Visual Attention on the iCub Humanoid Robot: Instructions for Use and New Perspectives

Author:

Pasquale Giulia,Mar Tanis,Ciliberto Carlo,Rosasco Lorenzo,Natale Lorenzo

Publisher

Frontiers Media SA

Subject

Artificial Intelligence,Computer Science Applications

Reference39 articles.

1. “Tracking people and their objects,”;Baumgartner,2013

2. “A binocular stereo algorithm for log-polar foveated systems,”;Bernardino,2002

3. “On the impact of learning hierarchical representations for visual recognition in robotics,”;Ciliberto,2013

4. “Reexamining Lucas-Kanade method for real-time independent motion detection: application to the iCub humanoid robot,”;Ciliberto,2011

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. iCub Knows Where You Look: Exploiting Social Cues for Interactive Object Detection Learning;2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids);2022-11-28

2. Learn Fast, Segment Well: Fast Object Segmentation Learning on the iCub Robot;IEEE Transactions on Robotics;2022-10

3. Event-driven proto-object based saliency in 3D space to attract a robot’s attention;Scientific Reports;2022-05-10

4. Weakly-Supervised Object Detection Learning through Human-Robot Interaction;2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids);2021-07-19

5. Fast Object Segmentation Learning with Kernel-based Methods for Robotics;2021 IEEE International Conference on Robotics and Automation (ICRA);2021-05-30

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