Abstract
Within the context of active vision, scant attention has been paid to the execution of motion saccades—rapid re-adjustments of the direction of gaze to attend to moving objects. In this paper we first develop a methodology for, and give real-time demonstrations of, the use of motion detection and segmentation processes to initiate “capture saccades” towards a moving object. The saccade is driven by both position and velocity of the moving target under the assumption of constant target velocity, using prediction to overcome the delay introduced by visual processing. We next demonstrate the use of a first order approximation to the segmented motion field to compute bounds on the time-to-contact in the presence of looming motion. If the bound falls below a safe limit, a “panic saccade” is fired, moving the camera away from the approaching object. We then describe the use of image motion to realize smooth pursuit, tracking using velocity information alone, where the camera is moved so as to null a single constant image motion fitted within a central image region. Finally, we glue together capture saccades with smooth pursuit, thus effecting changes in both what is being attended to and how it is being attended to. To couple the different visual activities of waiting, saccading, pursuing and panicking, we use a finite state machine which provides inherent robustness outside of visual processing and provides a means of making repeated exploration. We demonstrate in repeated trials that the transition from saccadic motion to tracking is more likely to succeed using position and velocity control, than when using position alone.
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Aloimonos, J., Weiss, I., and Bandyopadhyay, A. 1988. Active vision.International Journal of Computer Vision, l(4):333–356
Bajcsy, R. 1985. Active perception vs. passive perception. InProceedings of the 3rd Workshop on Computer Vision: Representation and Control, Bellaire MI. IEEE Computer Society Press, Silver Springs MD.
Bajcsy, R. 1988. Active perception.Proc. IEEE, 76:996–1005.
Bajcsy, R. and Campos, M. 1992. Active and exploratory perception.CVGIP: Image Understanding, 56(l):31–40.
Ballard, D.H. 1989. Behavioural constraints on computer vision. Image and Vision Computing, 7(1).
Ballard, D.H. 1991. Animate vision.Artificial Intelligence, 48: 57–86.
Ballard, D.H. and Brown, CM. 1992. Principles of animate vision.CVGIP: Image Understanding, 56(1):3–21.
Ballard, D.H. and Ozcandarli, A. 1988. Eye fixation and early vision: kinetic depth. InProceedings of the 2nd IEEE International Conference on Computer Vision, Tampa FL, IEEE Computer Society Press, Washington DC, p. 524.
Birnbaum, L., Brand, M., and Cooper, P. 1993. Looking for trouble: using causal semantics to direct focus of attention. InProceedings of the 4th International Conference on Computer Vision, Berlin, IEEE Computer Society Press, Los Alamitos, CA, pp. 49–56.
Brown, CM. 1990. Gaze control with interactions and delays.IEEE Trans. Sys. Man and Cybernet., TSMC-20(2):518–527.
Brown, CM. 1990. Prediction and cooperation in gaze control.Biological Cybernetics, 63:61–70.
Brown, CM., Ballard, D.H., Becker, T.G., Gans, R.F., Martin, N.G., Ohlson, T.J., Potter, R.D., Rimey, R.D., Tilley, D.G., and Whitehead, S.D. 1988. The Rochester Robot. Technical Report TR 257, Computer Science Department, University of Rochester, Rochester, NY.
Campani, M. and Verri, A. 1990. Computing optical flow from an overconstrained system of linear algebraic equations. InProceedings of the 3rd IEEE International Conference on Computer Vision, Osaka, Japan, IEEE Computer Society Press, Washington DC, pp. 22–26.
Campani, M. and Verri, A. 1992. Motion analysis from first-order properties of optical flow.CVGIP: Image Understanding, 56(1):90–107.
Carpenter, R.H.S. 1988.Movements of the Eyes. Pion Press, London.
Cipolla, R. and Blake, A. 1990. The dynamic analysis of apparent contours. InProceedings of the 3rd IEEE International Conference on Computer Vision, Osaka, Japan, IEEE Computer Society Press, Washington DC, pp. 616–632.
Cipolla, R. and Blake, A. 1992. Surface orientation and time to contact from image divergence and deformation. InProceedings of the 2nd European Conference on Computer Vision, Santa Margherita Ligure, Italy, Springer-Verlag, Berlin, pp. 187–202.
Clark, J.J. and Ferrier, N.J. 1988. Modal control of an attentive vision system. InProceedings of the 2nd International Conference on Computer Vision, Tampa FL, IEEE Computer Society Press, Washington DC, pp. 514–523.
Fennema, C.L. and Thompson, W.L. 1979. Velocity determination in scenes containing several moving objects.Computer Graphics and Image Processing, 9:301–315.
Fermueller, C. and Aloimonos, Y. 1993. The role of fixation in visual motion analysis.International Journal of Computer Vision, 11(2): 165–186.
Grosso, E. and Ballard, D.H. 1993. Head-centred orientation strategies in animate vision. InProceedings of the 4th IEEE International Conference on Computer Vision, Berlin, IEEE Computer Society Press, Washington DC, pp. 395–402.
Horn, B.K.P. and Schunck, B.G. 1981. Determining optical flow.Artificial Intelligence, 17:185–203.
Koenderink, J.J. and van Doorn, A.J. 1975. Invariant properties of the motion parallax field due to the movement of rigid bodies relative to an observer.Optica Acta, 22(9):773–791.
McLauchlan, P.F. and Murray, D.W. 1993. Active camera calibration for a head-eye platform using a variable state dimension filter. InSPIE Sensor Fusion VI, Boston.
McLauchlan, P.F. and Reid, I.D. 1993. A 2D vision system for real time gaze control. Technical Report WP3/Oxford/930112/2D Vision, Dept. of Engineering Science, University of Oxford.
McLauchlan, P.F., Reid, I.D., and Murray, D.W. 1992. Coarse motion for saccade control. In D. Hogg and R. Boyle (eds.),Proceedings of the 3rd British Machine Vision Conference, Leeds, UK, Springer-Verlag, pp. 357–366.
Nelson, R.C. 1991. Qualitative detection of motion by a moving observer. International Journal of Computer Vision, 7(1):33–46.
Olson, T.J. and Coombs, D.J. 1991. Real-time vergence control for binocular robots.International Journal of Computer Vision, 7(l):67–89.
Pahlavan, K. and Eklundh, J.-O. 1992. A head-eye system-analysis and design.CVGIP: Image Understanding, 56(l):41–56.
Rimey, R.D. and Brown, CM. 1992. Where to look next using a Bayes net: incorporating geometric relations. In G. Sandini (ed.), Proceedings of the 2nd European Conference on Computer Vision, Santa Margherita Ligure, Italy, Springer-Verlag, pp. 542–550.
Sharkey, P.M. and Murray, D.W. 1993. Coping with delays for realtime gaze control. InSPIE Sensor Fusion VI, Boston.
Sharkey, P.M., Murray, D.W., Vandevelde, S., Reid, I.D., and McLauchlan, P.F. 1993. A modular head/eye platform for realtime reactive vision.Mechatronics, 3(4): 517–535.
Sharkey, P.M., Reid, I.D., McLauchlan, P.F., and Murray, D.W. 1992. Real-time control of an active stereo head/eye platform. InProceedings of the 2nd International Conference on Automation, Robotics and Computer Vision, Singapore.
Swain, M.J. and Stricker, M.A. 1993. Promising directions in active vision.International Journal of Computer Vision, 11(2): 109–126.
Verri, A. and Poggio, T. 1987. Against quantitative optical flow. InProc. 1st Int. Conf. on Computer Vision, IEEE Computer Society Press, Washington DC, pp. 171–180.
Verri, A. and Poggio, T. 1989. Motion field and optical flow: qualitative properties.IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-11:490–498.
Yarbus, A.L. 1967.Eye Movements and Vision. Plenum, New York.
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Murray, D.W., Bradshaw, K.J., McLauchlan, P.F. et al. Driving saccade to pursuit using image motion. Int J Comput Vision 16, 205–228 (1995). https://doi.org/10.1007/BF01539627
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DOI: https://doi.org/10.1007/BF01539627