Abstract
This paper proposes a method to realize a 3D video system that can capture video data from multiple cameras, reconstruct 3D models, transmit 3D video streams via the network, and display them on remote PCs. All processes are done in real time. We represent a player with a simplified 3D model consisting of a single plane and a live video texture extracted from multiple cameras. This 3D model is simple enough to be transmitted via a network. A prototype system has been developed and tested at actual soccer stadiums. A 3D video of a typical soccer scene, which includes more than a dozen players, was processed at video rate and transmitted to remote PCs through the internet at 15–24 frames per second.
Similar content being viewed by others
References
Akenine-Moller, T. and Haines, E. 2002. Real-Time Rendering, AK Peters Ltd., ISBN 1568811829.
Antonini, G., Martinez, S.V., Bierlaire, M., and Thiran, J.P. 2006. Behavioral priors for detection and tracking of pedestrians in video sequences. International Journal of Computer Vision, 69(2):159–180.
Barnard, M. and Odobez, J.M. 2004. Robust playfield segmentation using MAP adaptation. In International Conference on Pattern Recognition, vol. 3, pp. 610–613.
Cheung, G.K.M., Kanade, T., Bouguet, J.Y., and Holler, M. 2000. A real time system for robust 3D voxel reconstruction of human motions. In Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR2000), pp. 714-729.
Cheng, K.M., Baker, S., and Kanade, T. 2005a. Shape-from-silhouette across time part I: Theory and algorithms. International Journal of Computer Vision, 62(3):221–247.
Cheng, K.M., Baker, S., and Kanade, T. 2005b. Shape-from-silhouette across time part II: Applications to human modeling and markerless motion tracking. International Journal of Computer Vision, 63(3):225–245.
Collins, R.T. 1996. A space-sweep approach to true multi-image matching. In Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’96), pp. 358–363.
Deutscher, J. and Reid, I. 2005. Articulated body motion capture by stochastic search. International Journal of Computer Vision, 61(2):185–205.
Efros, A.A., Berg, A.C., Mori, G., and Malik, J. 2003. Recognizing action at a distance. IEEE International Conference on Computer Vision, 2:726–733.
Figueroa, P., Leite, N., Barros, R.M.L, Cohen, I., and Medioni, G. 2004. Tracking soccer players using the graph representation. International Conference on Pattern Recognition, 4:787–790.
Iwase, S. and Saito, H. 2004. Parallel tracking of all soccer players by integrating detected positions in multiple view images. International Conference on Pattern Recognition, 4:751–754.
Kanade, T., Rander, P.W., and Narayanan, P.J. 1997. Virtualized reality: constructing virtual worlds from real scenes. IEEE Multimedia, 4(1):34–47.
Kim, T., Seo, Y., and Hong, K. 1998. Physics-based 3D position analysis of a soccer ball from monocular image sequences. In IEEE International Conference on Computer Vision, pp. 721–726.
Kitahara, I., Saito, H., Akimichi, S., Ono, T., Ohta Y., and Kanade, T. 2001. Large-scale virtualized reality. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2001), Technical Sketches.
Matusik, W., Buehler, C., Raskar, R., Gortler S.J., and McMillan, L. 2000. Image-based visual hulls. In ACM SIGGRAPH 2000, pp. 369–374.
Misu, T., Naemura, M., Zheng, W., Izumi, Y., and Fukui, K. 2002. Robust tracking of soccer players based on data fusion. In International Conference on Pattern Recognition, 1:556–561.
Moezzi, S., Katkere, A., Kuramura, D.Y., and Jain, R. 1996. Interactive three-dimensional digital video. In Proc. of IEEE International Conference on Multimedia Computing and Systems (ICMCS’96), pp. 358–361.
Narayanan, P.J., Rander, P., and Kanade, T. 1998. Constructing virtual worlds using dense stereo. In Proc. of the International Conference on Computer Vision (ICCV’98), pp. 3–10.
Ohno, Y., Miura, J., and Shirai, Y. 2000. Tracking players and estimation of the 3D position of a ball in soccer games. In International Conference on Pattern Recognition, vol 2, pp. 145–148.
Pan, Z. and Ngo, C.W. 2004. Novel seed selection for multiple objects detection and tracking. In International Conference on Pattern Recognition, vol 2, pp. 744–747.
Potmesil, M. 1987. Generating octree model of 3D objects from their silhouette in a sequence of images. Computer Vision, Graphics and Image Processing (CVGIP), 40:1–29.
Ramanan, D., Forsyth, A., and Zisserman, A. 2005. Strike a pose: tracking people by finding stylized poses. In IEEE Conference on Computer Vision and Pattern Recognition, vol 1, pp. 271–278.
Rosales, R. and Sclaroff, S. 2006. Combining generative and discriminative models in a framework for articulated pose estimation. International Journal of Computer Vision, 67(3):251–276.
Saito, H. and Kanade, T. 1999. Shapae reconstruction in projective grid space from large number of images. In Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR’99), pp. 49– 54.
Seitz, S.M. and Dyer, C.R. 1998. Photorealistic scene reconstruction by voxel coloring. In Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR’98), pp. 1067–1073.
Stauffer, C. and Grimson, W. 1999. Adaptive background mixture for real-time tracking. IEEE Conference on Computer Vision and Pattern Recognition, pp. 246–252.
Sugawara, S., Suzuki, G., Nagashima, Y., Matsuura, M., Tanigawa, H., and Morimichi, M. 1994. Interspace: Networked virtual world for virtual communications. IEICE Transaction on Information and Systems, E77-D(2):1344–1349.
Sullivan, S. and Ponce, J. 1998. Automatic model construction, pose estimation and objects recognition from photographs using triangular splines. In Proc. of the International Conference on Computer Vision (ICCV’98), pp. 510–516.
Szelisli, R. 1993. Rapid octree construction from image sequences. Computer Vision, Graphics and Image Processing (CVGIP), 58:23–32.
Takeuchi, T. and Valois, K.D. 2002. Motion sharpening in moving natural images. Journal of Vision, 2(7):377.
Veit, T., Cao, F., and Bouthemy, P. 2006. An a contrario decision framework for region-based motion detection. International Journal of Computer Vision, 68(2):163–178.
Veloso, M., Stone, P., Han, K., and Achim, S. 1998. The CMUnited-97 small-robot team. Robot Soccer World Cup I (RoboCup-97), Lecture Notes in Artificial Intelligence, pp. 242– 256.
Viola, P., Jones M.J., and Snow, D. 2005. Detecting pedestrians using patterns of motion and appearance. International Journal of Computer Vision, 63(2):153–161.
Wada, T., Wu, X., and Matsuyama, T. 2000. Homography based parallel volume intersection: Toward real-time volume reconstruction using active cameras. In Proc. of Computer Architectures for Machine Perception 2000, pp. 331–339.
Würmlin, S., Lamboray, E.O., Staadt, G., and Gross, M.H. 2002. 3D Video Recorder. Proceedings of Pacific Graphics ’02, IEEE Computer Society Press, pp. 325–334.
Yamada, A., Shirai, Y., and Miura, J. 2002. Tracking players and a ball in video image sequence and estimating camera parameters for 3D interpretation of soccer games. International Conference on Pattern Recognition, 1:303–306.
Yang, R., Kurashima, C., Nashel, A., Towles, H., Lastra, A., and Fuchs, H. 2002. Creating adaptive views for group video teleconferencing -an image-based approach. International Workshop on Immersive Telepresence (ITP 2002).
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Ohta, Y., Kitahara, I., Kameda, Y. et al. Live 3D Video in Soccer Stadium. Int J Comput Vis 75, 173–187 (2007). https://doi.org/10.1007/s11263-006-0030-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11263-006-0030-z