Attention control for robot vision

Focus of attention mechanisms for robot vision are discussed. A new method for neglecting low level filter responses from already modelled structures is presented. The method is based on a filtering technique termed normalized convolution. In one experiment, the robot is continuously moving its arm in the scene while tracking other objects. It is shown how the arm can be made "invisible" so that only the moving object of interest is detected. This makes tracking of objects much simpler. In another experiment, the attention of the system is shifted between objects by simply cancelling the mask of the object to be attended to. With this strategy the low level processes do not need to know the difference between a new object entering the scene and a mask being cancelled, and thus a complex communication structure between high and low levels is avoided.

[1]  Carl-Fredrik Westin,et al.  Normalized and differential convolution , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[2]  Gösta H. Granlund.  Integrated Analysis-Response Structures for Robotics Systems , 1988 .

[3]  Mohan M. Trivedi,et al.  Savic: A Simulation, Visualization and Interactive Control Environment for Mobile Robots , 1993, Int. J. Pattern Recognit. Artif. Intell..

[4]  C. Westin,et al.  Normalized and differential convolution , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[5]  John K. Tsotsos,et al.  An Attentional Prototype for Early Vision , 1992, ECCV.

[6]  Kjell Brunnström,et al.  Active Detection and Classsification of Junctions by Foveation with a Head-Eye System Guided by the Scale-Space Primal Sketch , 1992, ECCV.

[7]  M. Tistarelli,et al.  Direct estimation of time-to-impact from optical flow , 1991, Proceedings of the IEEE Workshop on Visual Motion.

[8]  Carl-Fredrik Westin,et al.  Prototyping, Visualization and Simulation Using the Application Visualization System , 1994 .

[9]  Dana H. Ballard,et al.  Animate Vision , 1991, Artif. Intell..

[10]  G. Granlund.  In search of a general picture processing operator , 1978 .

[11]  Eric L. Schwartz,et al.  Computational anatomy and functional architecture of striate cortex: A spatial mapping approach to perceptual coding , 1980, Vision Research.

[12]  C. Westin.  A Tensor Framework for Multidimensional Signal Processing , 1994 .

[13]  Christopher Brown,et al.  Gaze controls with interactions and decays , 1989, IEEE Trans. Syst. Man Cybern..

[14]  Carl-Johan Westelius,et al.  Focus of attention and gaze control for robot vision , 1995 .

[15]  Hans Knutsson,et al.  Issues in robot vision , 1994, Image Vis. Comput..

[16]  Hans Knutsson,et al.  Preattentive gaze control for robot vision , 1992 .

[17]  A. Lynn Abbott,et al.  Surface Reconstruction By Dynamic Integration Of Focus, Camera Vergence, And Stereo , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[18]  B. Julesz.  Early vision and focal attention , 1991 .

[19]  Mohan M. Trivedi,et al.  Mobile robots with articulated tracks and manipulators: intelligent control and graphical interface for teleoperation , 1993, Other Conferences.