Abstract
Pool and billiards are amongst a family of games played on a table with six pockets along the rails. This paper presents an augmented reality tool designed to assist unskilled or amateur players of such games. The system is based on a projector and a Kinect 2 sensor placed above the table, acquiring and processing the game on-the-fly. By using depth information and detecting the table’s rails (borders), the balls’ positions, the cue direction, and the strike of the ball, computations predict the resulting balls’ trajectories after the shot is played. These results—trajectories, visual effects, and menus—are visually output by the projector, making them visible on the snooker table. The system achieves a shot prediction accuracy of 98% when no bouncing occurs.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
Kinect2. Kinect for Windows. 2015. Available at http://www.microsoft.com/en-us/kinectforwindows/.
Höferlin, M.; Grundy, E.; Borgo, R.; Weiskopf, D.; Chen, M.; Griffiths, I. W.; Griffiths, W. Video visualization for snooker skill training. Computer Graphics Forum Vol. 29, No. 3, 1053–1062, 2010.
Jiang, R.; Parry, M. L.; Legg, P. A.; Chung, D. H. S.; Griffiths, I. W. Automated 3-D animation from snooker videos with information-theoretical optimization. IEEE Transactions on Computational Intelligence and AIin Games Vol. 5, No. 4, 337–345, 2013.
Ling, Y.; Li, S.; Xu, P.; Zhou, B. The detection of multi-objective billiards in snooker game video. In: Proceedings of the 3rd International Conference on Intelligent Control and Information Processing, 594–596, 2012.
Archibald, C.; Altman, A.; Greenspan, M.; Shoham, Y. Computational pool: A new challenge for game theory pragmatics. AI Magazine Vol. 31, No. 4, 33–41, 2010.
Landry, J.-F.; Dussault, J.-P.; Mahey, P. Billiards: An optimization challenge. In: Proceedings of the 4th International C* Conference on Computer Science and Software Engineering, 129–132, 2011.
Nierhoff, T.; Kourakos, O.; Hirche, S. Playing pool with a dual-armed robot. In: Proceedings of IEEE International Conference on Robotics and Automation, 3445–3446, 2011.
Leckie, W.; Greenspan, M. An event-based pool physics simulator. In: Lecture Notes in Computer Science, Vol. 4250. Van den Herik, H. J.; Hsu, S.-C.; Hsu, T.-S.; Donkers, H. H. L. M. Eds. Springer Berlin Heidelberg, 247–262, 2006.
Shih, C. Analyzing and comparing shot planning strategies and their effects on the performance of an augment reality based billiard training system. International Journal of Information Technology & Decision Making Vol. 13, No. 3, 521–565, 2014.
Shih, C.; Koong, C.-S.; Hsiung, P.-A. Billiard combat modeling and simulation based on optimal cue placement control and strategic planning. Journal of Intelligent & Robotic Systems Vol. 67, No. 1, 25–41, 2012.
ARPool. Augmented reality: Pool. 2015. Available at http://rcvlab.ece.queensu.ca/qridb/ARPOOL.html.
Alves, R.; Sousa, L.; Rodrigues, J. M. F. PoolLiveAid: Augmented reality pool table to assist inexperienced players. In: Proceedings of the 21st International Conference on Computer Graphics, Visualization and Computer Vision, 184–193, 2013.
Larsen, L. B.; Jensen, R. B.; Jensen, K. L.; Larsen, S. Development of an automatic pool trainer. In: Proceedings of the 2005 ACM SIGCHI International Conference on Advances in Computer Entertainment Technology, 83–87, 2005.
Ahmed, F.; Paul, P. P.; Gavrilova, M. L. DTW-based kernel and rank-level fusion for 3D gait recognition using Kinect. The Visual Computer Vol. 31, No. 6, 915–924, 2015.
Song, X.; Zhong, F.; Wang, Y.; Qin, X. Estimation of Kinect depth confidence through self-training. The Visual Computer Vol. 30, No. 6, 855–865, 2014.
Abedan Kondori, F.; Yousefi, S.; Liu, L.; Li, H. Head operated electric wheelchair. In: Proceedings of IEEE Southwest Symposium on Image Analysis and Interpretation, 53–56, 2014.
OpenPool. OpenPool. 2015. Available at http:// www.openpool.cc/.
Russ, J. C. The Image Processing Handbook, 6th edn. CRC press, 2011.
Suzuki, S.; KeiichiA be. Topological structural analysis of digitized binary images by border following. Computer Vision, Graphics, and Image Processing Vol. 30, No. 1, 32–46, 1985.
Duda, R. O.; Hart, P. E. Use of the Hough transformation to detect lines and curves in pictures. Communications of the ACM Vol. 15, No. 1, 11–15, 1972.
PoolLiveAid. PoolLiveAid Facebook. 2015. Available at https://www.facebook.com/Poolliveaid.
Legg, P. A.; Parry, M. L.; Chung, D. H. S.; Jiang, R. M.; Morris, A.; Griffiths, I. W.; Marshall, D.; Chen, M. Intelligent filtering by semantic importance for single-view 3D reconstruction from Snooker video. In: Proceedings of the 18th IEEE International Conference on Image Processing, 2385–2388, 2011.
Author information
Authors and Affiliations
Corresponding author
Additional information
L. Sousa is a researcher at the University of the Algarve with a master degree in electrical and electronic engineering. He is a member of the LARSyS (ISR-Lisbon) laboratory and he is the co-author of 14 scientific publications. His major interests lie in electronic systems, embedded systems, and computer vision.
R. Alves has a master degree in electric and electronic engineering. He is a researcher at the University of the Algarve working with depth sensors. He is a member of the LARSyS (ISRLisbon) laboratory and he is the coauthor of 9 scientific publications. He also spends some of his time developing other electronics and programming projects.
J. M. F. Rodrigues graduated in electrical engineering in 1993, got his M.Sc. degree in computer systems engineering in 1998, and achieved a Ph.D. degree in electronics and computer engineering in 2008 from the University of the Algarve, Portugal. He is an adjunct professor at Instituto Superior de Engenharia, also in the University of the Algarve, where he has lectured computer science and computer vision since 1994. He is a member of the LARSyS (ISR-Lisbon) laboratory, CIAC and the associations APRP, IAPR and ARTECH. He has participated in 14 financed scientific projects, and he is the co-author of more than 120 scientific publications. His major research interests lie in computer and human vision, assistive technologies, and human–computer interaction.
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0), which permits use, duplication, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
About this article
Cite this article
Sousa, L., Alves, R. & Rodrigues, J.M.F. Augmented reality system to assist inexperienced pool players. Comp. Visual Media 2, 183–193 (2016). https://doi.org/10.1007/s41095-016-0047-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41095-016-0047-3