Summary
We present a biologically inspired active vision system that incorporates two modes of perception. A peripheral mode provides a broad and coarse perception of where mass is in the scene in the vicinity of the current fixation point, and how that mass is moving. It involves fusion of actively acquired depth data into a 3D occupancy grid. A foveal mode then ensures coordinated stereo fixation upon mass/objects in the scene, and enables extraction of the mass/object using a maximum a-posterior probability zero disparity filter. Foveal processing is limited to the vicinity of the camera optical centres. Results for each mode and both modes operating in parallel are presented. The regime operates at approximately 15Hz on a 3GHz single processor PC.
National ICT Australia is funded by the Australian Department of Communications, Information Technology and the Arts and the Australian Research Council through Backing Australia’s ability and the ICT Centre of Excellence Program.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
J. Aloimonos, I. Weiss, and A. Bandyopadhyay, “Active vision,” in IEEE Int. Journal on Computer Vision, 1988.
N. Apostoloff and A. Zelinsky, “Vision in and out of vehicles: Integrated driver and road scene monitoring,” IEEE Int. Journal of Robotics Research, vol. 23, no. 4, 2004.
R. Bajczy, “Active perception,” in IEEE Int. Journal on Computer Vision, 1988.
D. Ballard, “Animate vision,” in Artificial Intelligence, 1991.
J. Banks and P. Corke, “Quantitative evaluation of matching methods and validity measures for stereo vision,” IEEE Int. Journal of Robotics Research, vol. 20, no. 7, 1991.
Y. Boykov, O. Veksler, and R. Zabih, “Markov random fields with efficient approximations,” Computer Science Department, Cornell University Ithaca, NY 14853, Tech. Rep. TR97-1658, 3 1997.
A. Dankers, N. Barnes, and A. Zelinsky, “Active vision-rectification and depth mapping,” in Australian Conf. on Robotics and Automation, 2004.
—, “Active vision for road scene awareness,” in IEEE Intelligent Vehicles Symposium, 2005.
A. Dankers and A. Zelinsky, “Driver assistance: Contemporary road safety,” in Australian Conf. on Robotics and Automation, 2004.
A. Elfes, “Using occupancy grids for mobile robot perception and navigation,” IEEE Computer Magazine, 6 1989.
L. Fletcher, N. Barnes, and G. Loy, “Robot vision for driver support systems,” in IEEE Int. Conf. on Intelligent Robots and Systems, 2004.
L. Ford and D. Fulkerson, Flows in Networks. Princeton University Press, 1962.
S. Geman and D. Geman, “Stochastic relaxation, gibbs distributions, and the bayesian restoration of images,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, 1984.
G. Grubb, A. Zelinsky, L. Nilsson, and M. Rilbe, “3d vision sensing for improved pedestrian safety,” in IEEE Intelligent Vehicles Symposium, 2004.
R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, Second Edition. Cambridge University Press, 2004.
S. Kagami, K. Okada, M. Inaba, and H. Inoue, “Realtime 3d depth flow generation and its application to track to walking human being,” in IEEE Int. Conf. on Robotics and Automation, 2000.
V. Kolmogorov and R. Zabih, “Multi-camera scene reconstruction via graph cuts,” in Europuan Conf. on Comupter Vision, 2002.
—, “What energy functions can be minimized via graph cuts?” in Europuan Conf. on Comupter Vision, 2002.
G. Loy and N. Barnes, “Fast shape-based road sign detection for a driver assistance system,” in IEEE Int. Conf. on Intelligent Robots and Systems, 2004.
N. Pettersson and L. Petersson, “Online stereo calibration using fpgas,” in IEEE Intelligent Vehicles Symposium, 2005.
E. Schwartz, “A quantitative model of the functional architecture of human striate cortex with application to visual illusion and cortical texture analysis,” in Biological Cybernetics, 1980.
H. Truong, S. Abdallah, S. Rougeaux, and A. Zelinsky, “A novel mechanism for stereo active vision,” in Australian Conf. on Robotics and Automation, 2000.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dankers, A., Barnes, N., Zelinsky, A. (2006). Bimodal Active Stereo Vision. In: Corke, P., Sukkariah, S. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 25. Springer, Berlin, Heidelberg . https://doi.org/10.1007/978-3-540-33453-8_8
Download citation
DOI: https://doi.org/10.1007/978-3-540-33453-8_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33452-1
Online ISBN: 978-3-540-33453-8
eBook Packages: EngineeringEngineering (R0)