Abstract
We propose in this paper an active vision approach for performing the 3D reconstruction of polyhedral scenes. To perform the reconstruction we use a structure from controlled motion method which allows an accurate estimation of primitive parameters. As this method is based on particular camera motions, perceptual strategies able to appropriately perform a succession of such individual primitive reconstructions are proposed in order to recover the complete spatial structure of complex scenes. The algorithm described in this paper is based on the use of a prediction/verification scheme managed using decision theory and Bayes nets. It allows the visual system to get a more complete high level description of the scene.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
J.M. Agosta. The structure of Bayes nets for vision recognition. In Proc. of 4th Workshop on Uncertainty in Artificial Intelligence, Minneapolis, Aug. 1988.
H. Buxton, S. Gong. Visual surveillance in a dynamic and uncertain world. Artificial Intelligence, 78(1-2):431–459, Oct. 1995.
F. Chaumette, S. Boukir, P. Bouthemy, D. Juvin. Structure from controlled motion. IEEE PAMI, 18(5):492–504, May 1996.
D. Djian, P. Probert, P. Rives. Active sensing using Bayes nets. In Proc. of Int. Conf. on Advanced Robotics, ICAR'95, pages 895–902, Sant Feliu de Guixols, Spain, Sep. 1995.
B. Espiau, F. Chaumette, P. Rives. A new approach to visual servoing in robotics. IEEE Trans. on Robotics and Automation, 8(3):313–326, June 1992.
E. Marchand. Stratégies de perception par vision active pour la reconstruction et l'exploration de scènes statiques. PhD thesis, Univ. of Rennes 1, IRISA, June 1996.
E. Marchand, F. Chaumette. Controlled camera motions for scene reconstruction and exploration. In CVPR'96, pages 169–176, San Francisco, June 1996.
J. Pearl. Probabilistic reasoning in intelligent systems: Networks of plausible inference. Morgan Kaufmann Publisher Inc., 1988.
R.D. Rimey, C. Brown. Control of selective perception using Bayes nets and decision theory. IJCV, 12(2/3):173–207, Apr. 1994.
S. Sarkar, K. Boyer. Integration, inference, and management of spatial information using Bayesian networks: perceptual organization. IEEE PAMI, 15(3):256–274, Mar. 1993.
K. Tarabanis, P.K. Allen, R. Tsai. A survey of sensor planning in computer vision. IEEE Trans. on Robotics and Automation, 11(1):86–104, Feb. 1995. *** DIRECT SUPPORT *** A0008188 00022
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Marchand, É., Chaumette, F. (1997). A Bayes nets-based prediction/verification scheme for active visual reconstruction. In: Chin, R., Pong, TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63930-6_178
Download citation
DOI: https://doi.org/10.1007/3-540-63930-6_178
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63930-5
Online ISBN: 978-3-540-69669-8
eBook Packages: Springer Book Archive