Robot Head Pose Detection and Gaze Direction Determination Using Local Invariant Features

Gaze direction determination can be a powerful anticipatory perceptual mechanism for determining the next action of other individuals, humans or robots. It can allow cooperation, synchronization or competition between robots. This is of particular importance in the case of anthropomorphic robots, which in addition of having a human-like body, should behave as humans and have similar attention mechanisms for tracking and gazing other individuals and objects. We address this problem by proposing a gaze direction determination system for robots. This system is based primarily on a robot head pose detection system that consists of two processing stages: computation of scale-invariant local descriptors of the scene and matching of these descriptors against descriptors of robot head prototypes already stored in a database. These prototypes correspond to images of robot heads taken under different view angles. After the robot head pose is detected, the robot gaze direction is determined by a composed coordinate transformation that considers the three-dimensional pose of the observing robot's camera, the detected robot head pose with respect to the observing camera, and the head model of the observed robot. Results of the successful application of the proposed system in real robots are presented.

[1]  Cordelia Schmid,et al.  A Comparison of Affine Region Detectors , 2005, International Journal of Computer Vision.

[2]  Jian-Gang Wang,et al.  Eye gaze estimation from a single image of one eye , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[3]  Tetsuo Ono,et al.  Development of an Interactive Humanoid Robot "Robovie" - An interdisciplinary approach , 2001, ISRR.

[4]  Qiang Ji,et al.  Real-Time Eye, Gaze, and Face Pose Tracking for Monitoring Driver Vigilance , 2002, Real Time Imaging.

[5]  Javier Ruiz-del-Solar,et al.  Robust Object Recognition Using Wide Baseline Matching for RoboCup Applications , 2007, RoboCup.

[6]  Javier Ruiz-del-Solar,et al.  Face Recognition for Human-Robot Interaction Applications: A Comparative Study , 2009, RoboCup.

[7]  Cordelia Schmid,et al.  Scale & Affine Invariant Interest Point Detectors , 2004, International Journal of Computer Vision.

[8]  Naoki Mukawa,et al.  FreeGaze: a gaze tracking system for everyday gaze interaction , 2002, ETRA.

[9]  Christopher Hunt,et al.  Notes on the OpenSURF Library , 2009 .

[10]  Andrew Zisserman,et al.  Automated location matching in movies , 2003, Comput. Vis. Image Underst..

[11]  George C. Stockman,et al.  Real-time tracking of face features and gaze direction determination , 1998, Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201).

[12]  K. Nakadai,et al.  Real-Time Auditory and Visual Multiple-Object Tracking for Robots , 2001, IJCAI 2001.

[13]  James J. Little,et al.  Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks , 2002, Int. J. Robotics Res..

[14]  Javier Ruiz-del-Solar,et al.  Gaze Direction Determination of Opponents and Teammates in Robot Soccer , 2005, RoboCup.

[15]  Cordelia Schmid,et al.  A performance evaluation of local descriptors , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[17]  Cordelia Schmid,et al.  Local Grayvalue Invariants for Image Retrieval , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Tetsuo Ono,et al.  Development and evaluation of an interactive humanoid robot "Robovie" , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[19]  Luc Van Gool,et al.  Edinburgh Research Explorer Simultaneous Object Recognition and Segmentation by Image Exploration , 2022 .

[20]  David G. Lowe,et al.  Local feature view clustering for 3D object recognition , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[21]  Antonio García Dopico,et al.  A Precise Eye-Gaze Detection and Tracking System , 2003, WSCG.

[22]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[23]  Javier Ruiz-del-Solar,et al.  A Fast Probabilistic Model for Hypothesis Rejection in SIFT-Based Object Recognition , 2006, CIARP.