Abstract
A very important problem in computer vision is the matching of features extracted from pairs of images. At this proposal, a new neural network, the Double Asynchronous Competitor (DAC) is presented. It exploits the self-organization for solving the matching as a pattern recognition problem. As a consequence, a set of attributes is required for each image feature. The network is able to find the variety of the input space. DAC exploits two intercoupled neural networks and outputs the matches together with the occlusion maps of the pair of frames taken in consideration. DAC can also solve other matching problems.
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
Faugeras, O.: Three-Dimensional Computer Vision: a Geometric Viewpoint. MIT Press, Cambridge, Massachusetts (1993)
Hopfield, J.: Neural networks and physical systems with emergent collective computational abilities. Proc. Nat. Acad. Sci. 79, 2554–2558 (1982)
Zhou, Y., Chellappa, R.: Artificial Neural Networks for Computer Vision. Research Notes in Neural Computing, vol. 5. Springer, Heidelberg (1992)
Sarigianidis, G., Pycock, D.: Motion correspondence using a neural network. In: British Machine Vision Conference, pp. 649–658 (1993)
Nasrabadi, N., Choo, C.: Hopfield network for stereo vision correspondence. IEEE Trans. on Neural Networks 3(1), 5–12 (1992)
Bellando, J., Kothari, R.: On image correspondence using topology preserving mappings. In: Proc. Int. Conf. On Neural Networks, Washington, DC (USA), pp. 1784–1789 (June 1996)
Kohonen, T.: Self-Organization and Associative Memory. Springer, Berlin (1989)
Smith, S., Brady, J.: Susan-a new approach to low level image processing. International Journal of Computer Vision 23(1), 45–78 (1997)
Weng, J., Huang, T., Ahuja, N.: Motion and Structure from Image Sequences. Springer Series in Information Sciences. Springer, Heidelberg (1993)
Moravec, H.: Visual mapping by a robot rover. In: Proc. Of the 6th Int. Joint Conf. On Artificial Intelligence, pp. 598–600 (1979)
Beaudet, P.: Rotational invariant image operators. In: Proc. Of the Int. Conf. On Pattern Recognition, pp. 579–583 (1978)
Cirrincione, G.: A Neural Approach to the Structure from Motion Problem. PhD thesis, LIS INPG Grenoble (December 1998)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cirrincione, G., Cirrincione, M. (2007). Neural Networks for Matching in Computer Vision. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74819-9_85
Download citation
DOI: https://doi.org/10.1007/978-3-540-74819-9_85
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74817-5
Online ISBN: 978-3-540-74819-9
eBook Packages: Computer ScienceComputer Science (R0)