3D Modeling of the Relievo Based on the Computer Active Vision

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International Journal of Advanced Network, Monitoring and Controls

Xi'an Technological University

Subject: Computer Science , Software Engineering

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VOLUME 1 , ISSUE 2 (December 2016) > List of articles

3D Modeling of the Relievo Based on the Computer Active Vision

Wu Gui / Tao Jun

Keywords : 3D Modeling, small relieve, calibration, slide projector, computer active vision, photogrammetry

Citation Information : International Journal of Advanced Network, Monitoring and Controls. Volume 1, Issue 2, Pages 68-75, DOI: https://doi.org/10.2991/mcei-16.2016.240

License : (CC BY-NC-ND 4.0)

Published Online: 08-April-2018

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ABSTRACT

At present, the 3D modeling of the small relievo which is lack of real texture or no real texture is a huge difficulty and challenge. The paper provides a good way based on the computer active vision. The slide projector as an active sensor is steered in the principle of the traditional binocular vision. The slide projector could supply the designed texture features to the small relieve, which is easy to be extracted out and matched well because they are clear and stable. The space forward intersection method can compute out the space coordinates of the texture features. The final 3D model is built by connecting the neighbor space points. The 3D modeling of the small relievo based on the computer active vision is proved to be effective and practical by the experimental data and results.

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REFERENCES

Guiying Li, B. Junlong Liu, Chunhui Jiang, and Ke Tang, “Relief Impression Imamge Detection : Unsupervised Extracting Objrects Directly From Feature Arrangements,” Phil. Trans. Roy. Soc. London, vol. A247, pp. 529-551, January 2016.

 

O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, Z. Huang, et al, “Image large scale visual recognition challenge,” International Journal of Computer Vision, 2014, pp.1-42.

 

R. Girshick, J. Donahue, T. Darrell, and J. Malik, “Rich feature hierarchies ofr accurate object detection and semantic segmentation,” in Computer Vision and Pattern Recognition,, 2014, pp. 580-587.

 

J. R. Uijlings, K. E. van de Sande, T. Gevers, and A. W. smeulders, “Selective search for object recognition,” International journal of computer vision, vol. 104, no. 2, pp. 154-171, 2013.

 

H. O. Song, R. Girshick, S. Jegelka, J. Mairal, Z. Harchaoui, and T. Darrell, “On learning to localize objects with minimal supervision,”in Processing of the International Conference on Machine Learning, 2014.

 

Y. Yorozu, M. Hirano, K. Oka, and Y. Tagawa, “Binarized normed gradients for objectness estimation,” in Computer Visiion and Pattern Recognition, 2014, pp. 3286-3293.

 

A. Ghodrati, A. Diba, M. Pedersoli, T. Tuytelaars, and L. Van Gool, “Hunting objects by cascading deep convolutional layers,” in Processing of the IEEE International Conference on Computer Vision, 2015, pp, 2578-2586.

 

C. –W. Chou, O. Teytaud, S. –J. Yen, “Active object localization with deep reinforcement learning,” Volume 6624 of the series Lecture Notes in Computer Science pp 3273-3282, 2011.

 

Yuxia Sun, Shenyang, China, Cheng Liu, Hongkun Qiu, “Delving deep into rectifiers surpassing human level performance on imagenet classification,” in Computer Visiion and Pattern Recognition, pp. 1178 – 1182, 2013.

 

Jun Tao, “3D modeling of small object based on the projector-camera system,” in Kybernetes, Vol.41, No.9, 1269-1276, 2012.

 

Yen Shi-Jim, Yang Jung-Kuei, “A trainable system for object detection.” International Journal of Computer Vision, Vol.3, No.2, 100-118, 2011.

 

Sharma, S., Kobti, Z., Goodwin, S., “Knowledge generation for improving simulations in UCT for general game playing,” In: Wobcke, W., Zhang, M. (eds.) AI 2008. LNCS (LNAI), vol. 5360, pp. 49–55. Springer, Heidelberg, 2012.

 

Jun Tao, “Development and application of functionally gradient materials,” in Processing of International conference on industrial control and electronics engineering, 1022-1025, 2012.

 

Qiao Zhihua, Yang Ming, Wang Zijuan, “Visualizing and understanding convolutional networks,” in Computer Vision- ECCV, pp. 679-682, 2014.

 

Rolet, P., Sebag, M., Teytaud, O., “Integrated recognition, localization and detection using convolutional networks,” In: Proceedings of the ECML Conference, pp. 1255-1263, 2012.

 

Jun Tao, “Design and visualization of optical feedback laser based on computer vision,” in Processing of International conference on industrial control and electronics engineering, 1030-1032, 2012.

 

De Mesmay, F., Rimmel, A., Voronenko, Y., Püschel, M., “Convolutional feature masking for joint object and stuff segmentation,” In ACM International Conference Proceeding Series, vol. 382, p. 92. ACM, New York, 2013.

 

Lee, C.-S., Wang, M.-H., Chaslot, G., Hoock, J.-B., Rimmel, A., Teytaud, O., Tsai, S.-R., Hsu, S.- C., Hong, T.-P., “The pascal visual object classes challenge: A retrospective,” International Journal of Computer Vision, vol. 111, no. 1, pp, 98-136, 2014.

 

Jun Tao, “Face reconstruction based on camera-projector system,” in Processing of International conference on industrial control and electronics engineering, 1026-1029, 2012.

 

Chaslot, G., Winands, M., Uiterwijk, J., van den Herik, H., Bouzy, B., “Progressive Strategies for Monte-Carlo Tree Search,” In Proceedings of the 10th Joint Conference on Information Sciences (JCIS 2007), pp. 655–661. World Scientific Publishing Co. Pte. Ltd., Singapore, 2013.

 

Auer, P., “Using confidence bounds for exploitation-exploration trade-offs,” in The Journal of Machine Learning Research 3, 397–422, 2013.

 

Bourki, A., Chaslot, G., Coulm, M., Danjean, V., Doghmen, H., Hoock, J.-B., Hérault, T., Rimmel, A., Teytaud, F., Teytaud, O., Vayssière, P., Yu, Z., “Scalability and parallelization of monte-carlo tree search,” In Proceedings of Advances in Computer Games 13, 2010.

 

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