Skip to main content


Professional and Habitual Three Dimensional model of Car with outline and Structural Stereotypes

Issue Abstract

Abstract
While estimating the depth of object within each high quality tasks related to two dimensional and three dimensional conversions. This type of stereo conversion approach automatically estimates the two dimensional and three dimensional for corresponding the proposed depth that defines such dimensional models. Target object would be identical which provides deep view of the silhouette of object using strong depth. In a traditional model for three dimensional model generating the detailed knowledge of initial view of objects having structural design and matches the image position. It combines various sequences of images that have different views which vary with its perspective. It not only  eployed on images also with shadow of the car moving in front by comparing with the specified cars shadow and model. Applying different methods for generating the data utilizes  the high quality of different dimensional conversions.
Keywords: Depth Estimation, dimensional conversions, Contour Model and stereo  conversion.


Author Information
V.Vidhya
Issue No
3
Volume No
2
Issue Publish Date
05 Mar 2022
Issue Pages
1-21

Issue References

[1] O. Wang, M. Lang, M. Frei, A. Hornung, A. Smolic, and M. Gross, “Stereobrush: Interactive 2d to 3d conversion using discontinuous warps,” in Proc. EUROGRAPHICS Symp. SketchBased Interfaces Model., 2011, pp. 45–74.
[2] M. Guttmann, L. Wolf, and D. Cohen-Or, “Semi-automatic stereo extraction from video footage,” in Proc. IEEE 12th Int. Conf. Comput. Vis., Oct. 2009, pp. 136–142.
[3] R. B. Ribera, S. Choi, Y. Kim, J. Lee, and J. Noh, “Video panorama for 2d to 3d conversion,” Comput. Graph. Forum, vol. 31, no. 7, pp. 2067–2076, 2012.
[4] B. Ward, S. B. Kang, and E. Bennett, “Depth director: A system for adding depth to movies,” IEEE Comput. Graph. Appl., vol. 31, no. 1, pp. 36–48, Jan./Feb. 2011.
[5] A. P. V. Pernis and M. S. DeJohn, “Dimensionalization: Converting 2d films to 3d,” in Proc. Stereoscopic Displays and Appl. XIX, vol. 6803, pp. 68 030T-68 030T-5.
[6] H. Hwang, K. Kim, R. B. i. Ribera, and J. Noh, “Stereoscopic image generation of background terrain scenes,” Comput. Animation Virtual Worlds, vol. 22, nos. 2-3, pp. 317–323, 2011.
[7] A. McKenzie, E. Vendrovsky, and J. Noh, “Terrain geometry from monocular image sequences.” J. Comput. Sci. Eng., vol. 2, no. 1, pp. 98–108, 2008.
[8] B. M. Oh, M. Chen, J. Dorsey, and F. Durand, “Image-based modeling and photo editing,” in Proc. 28th Annu. Conf. Computer Graphics and Interactive Techniques, ser. SIGGRAPH ’01, New York, NY, USA: ACM, 2001, pp. 433–442.
[9] V. Blanz and T. Vetter, “A morphable model for the synthesis of 3d faces,” in Proc. 26th Annu. Conf. Computer Graphics and Interactive Techniques, ser. SIGGRAPH ’99, ACM, 1999, pp. 187–194.
[10] M. Leotta and J. Mundy, “Predicting high resolution image edges with a generic, adaptive, 3-d vehicle model,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2009, pp. 1311– 1318.
[11] P. Guan, A. Weiss, A. O. Balan, and M. J. Black, “Estimating human shape and pose from a single image,” in Proc. Int. Conf. Comput. Vis., 2009, pp. 1381–1388.