Abstract
This paper introduces the computer vision to 3D reconstruction of the object. A novel method is developed, which adopts the digital camera as the sensor and uses the techniques of image processing and vision calculation synthetically to realize the untouched 3D measurement. The binocular measurement theory and the camera calibration based on the neural network are also described. Finally, we give the procedures of the binocular 3D reconstruction and simulate a case with Matlab 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
Wang, X., Ye, M., Wang, X., Wang, H.: Binocular Vision Sensor Modeling Based on Neural Network. Optical Instruments 24, 42–46 (2002)
Zhao, Q., Sun, Z., Lan, L.: Neural Network Technique in Camera Calibration. Control and Decision 17, 336–338 (2002)
Smith, S.M., Brady, J.M.: SUSAN-A New Approach to Low Level Image Processing, Internal Technical Report TR95SMS1c (1995)
Lin, M., Wang, X., Guan, X.: Research on the Feature Extraction for Image Based on Differential Code. Yiqi Yibiao Xuebao 25, 465–467 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lin, M., Zhao, Y., Guan, Z., Ding, F., Xu, Q., Wang, X. (2005). Binocular 3D Reconstruction Based on Neural Network. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_123
Download citation
DOI: https://doi.org/10.1007/11427445_123
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25913-8
Online ISBN: 978-3-540-32067-8
eBook Packages: Computer ScienceComputer Science (R0)