Augmented reality system to assist inexperienced pool players

L. Sousa; R. Alves; J. M. F. Rodrigues

doi:10.1007/s41095-016-0047-3

Computational Visual Media 2016, 2(2): 183-193 https://doi.org/10.1007/s41095-016-0047-3

Research Article |

Open Access | Issue | Published: 26 April 2016

Augmented reality system to assist inexperienced pool players

Show Author's Information Hide Author's Information L. Sousa^¹(

), R. Alves^¹, J. M. F. Rodrigues^²

1 LARSyS and Institute of Engineering, University of the Algarve, 8005-139 Faro, Portugal.

2 LARSyS, CIAC and Institute of Engineering, University of the Algarve, 8005-139 Faro, Portugal.

Keywords:

computer vision, augmented reality (AR), Kinect, pool game

Cite this article:

Sousa L, Alves R, Rodrigues JMF. Augmented reality system to assist inexperienced pool players. Computational Visual Media, 2016, 2(2): 183-193. https://doi.org/10.1007/s41095-016-0047-3

Download citation

EndNote(RIS)

BibTeX

604

Views

Downloads

Citations

Crossref

N/A

WoS

Scopus

CSCD

Abstract Full text About this article

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.

Full text

Abstract

Full text

Outline

About this article

Augmented reality system to assist inexperienced pool players

Show Author's information Hide Author's Information L. Sousa^¹(

), R. Alves^¹, J. M. F. Rodrigues^²

1 LARSyS and Institute of Engineering, University of the Algarve, 8005-139 Faro, Portugal.

2 LARSyS, CIAC and Institute of Engineering, University of the Algarve, 8005-139 Faro, Portugal.

Abstract

Keywords: computer vision, augmented reality (AR), Kinect, pool game

References(22)

[1]

Kinect2. Kinect for Windows. 2015. Available at http://www.microsoft.com/en-us/kinectforwindows/.

[2]

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.

DOI Google Scholar

[3]

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 AI in Games Vol. 5, No. 4, 337-345, 2013.

DOI Google Scholar

[4]

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.

DOI

[5]

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.

DOI Google Scholar

[6]

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.

DOI

[7]

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.

DOI

[8]

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.

[9]

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.

DOI Google Scholar

[10]

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.

DOI Google Scholar

[11]

ARPool. Augmented reality: Pool. 2015. Available at http://rcvlab.ece.queensu.ca/qridb/ARPOOL.html.

[12]

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.

[13]

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.

DOI

[14]

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.

DOI Google Scholar

[15]

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.

DOI Google Scholar

[16]

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.

DOI

[17]

OpenPool. OpenPool. 2015. Available at http:// www.openpool.cc/.

[18]

Russ, J. C. The Image Processing Handbook, 6th edn. CRC press, 2011.

[19]

Suzuki, S.; Keiichi A be. Topological structural analysis of digitized binary images by border following. Computer Vision, Graphics, and Image Processing Vol. 30, No. 1, 32-46, 1985.

DOI Google Scholar

[20]

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.

DOI Google Scholar

[21]

PoolLiveAid. PoolLiveAid Facebook. 2015. Available at https://www.facebook.com/Poolliveaid.

[22]

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.

DOI

About this article

Publication history

Acknowledgements

Rights and permissions

Publication history

Revised: 24 December 2015

Accepted: 25 February 2016

Published: 26 April 2016

Issue date: June 2016

Copyright

Acknowledgements

This work was partly supported by the Portuguese Foundation for Science and Technology (FCT), project LARSyS UID/EEA/50009/2013, and the INALUX company (http://www.inalux.com/). We also thank the anonymous reviewers for their very significant and useful contributions to the paper.

Rights and permissions

This article is published with open access at Springerlink.com

The articles published in this journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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.

Other papers from this open access journal are available free of charge from http://www.springer.com/journal/41095. To submit a manuscript, please go to https://www. editorialmanager.com/cvmj.