Integrating visual exploration and visual search in robotic visual attention: The role of human-robot interaction

A common characteristics of the computational models of visual attention is they execute the two modes of visual attention (visual exploration and visual search) separately. This makes a visual attention model unsuitable for real-world robotic applications. This paper focuses on integrating visual exploration and visual search in a common framework of visual attention and the challenges resulting from such integration. It proposes a visual attention-oriented speech-based human robot interaction framework which helps a robot to switch back-and-forth between the two modes of visual attention. A set of experiments are presented to demonstrate the performance of the proposed framework.

[1]  Fakhri Karray,et al.  A Probabilistic Model of Overt Visual Attention for Cognitive Robots , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[2]  Minoru Asada,et al.  Acquisition of joint attention through natural interaction utilizing motion cues , 2007, Adv. Robotics.

[3]  Jannik Fritsch,et al.  A multi-modal object attention system for a mobile robot , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[5]  H. Ishiguro,et al.  Multimodal joint attention through cross facilitative learning based on μX principle , 2008, 2008 7th IEEE International Conference on Development and Learning.

[6]  James R. Williamson,et al.  Gaussian ARTMAP: A Neural Network for Fast Incremental Learning of Noisy Multidimensional Maps , 1996, Neural Networks.

[7]  Katharina J. Rohlfing,et al.  Computational Analysis of Motionese Toward Scaffolding Robot Action Learning , 2009, IEEE Transactions on Autonomous Mental Development.

[8]  T. Duckett,et al.  VOCUS : A Visual Attention System for Object Detection and Goal-directed Search , 2010 .

[9]  Olivier Stasse,et al.  A Visual Attention Framework for Search Behavior by a Humanoid Robot , 2006, 2006 6th IEEE-RAS International Conference on Humanoid Robots.

[10]  Lijin Aryananda.  Attending to Learn and Learning to Attend for a , 2006, 2006 6th IEEE-RAS International Conference on Humanoid Robots.

[11]  Garrison W. Cottrell,et al.  Visual saliency model for robot cameras , 2008, 2008 IEEE International Conference on Robotics and Automation.

[12]  Simone Frintrop,et al.  Attentional Landmarks and Active Gaze Control for Visual SLAM , 2008, IEEE Transactions on Robotics.

[13]  Rajesh P. N. Rao,et al.  Towards a Real-Time Bayesian Imitation System for a Humanoid Robot , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[14]  Christof Koch,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .