International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 31 | Number 1 | Year 2016 | Article Id. IJCTT-V31P113 | DOI : https://doi.org/10.14445/22312803/IJCTT-V31P113

Smartphone-based 3D Orientation Estimation for Virtually any Published PC Game

Anas Fattouh

Citation :

Anas Fattouh, "Smartphone-based 3D Orientation Estimation for Virtually any Published PC Game," International Journal of Computer Trends and Technology (IJCTT), vol. 31, no. 1, pp. 70-73, 2016. Crossref, https://doi.org/10.14445/22312803/IJCTT-V31P113

Abstract

Modern smartphone devices provide valuable sensing capabilities that can be used in many context aware applications. Some applications need special sensing data that cannot be obtained directly from existing sensors or the available data is not reliable. This paper presents a method to derive an Android smartphone’s 3D orientation from accelerometer, gyroscope and magnetometer data. The obtained orientation cab then be used to control virtually any published PC game. An experiment is provided as a proof of concept where a user can control a MIT Scratch PC game from his Android smartphone device.

Keywords

Smartphone device, motion sensors, accelerometer, gyroscope, magnetometer, orientation, MIT Scratch, PC game

References

[1] I. R. Félix, L. A. Castro, L.-F. Rodríguez, and É. C. Ruiz, "Mobile Phone Sensing: Current Trends and Challenges," in Ubiquitous Computing and Ambient Intelligence. Sensing, Processing, and Using Environmental Information, ed: Springer, 2015, pp. 369-374.
[2] R. Meier, Professional Android 4 application development: John Wiley & Sons, 2012.
[3] Dr. Sanjeev Dhawan, Nishu Dhundwal. "Real Time and Past Positional Location Analysis of Friends in a Social Network Using Smart Devices". International Journal of Computer Trends and Technology (IJCTT) V14(3):121- 124, Aug 2014.
[4] D. Acharjee, A. Mukherjee, J. Mandal, and N. Mukherjee, "Activity recognition system using inbuilt sensors of smart mobile phone and minimizing feature vectors," Microsystem Technologies, pp. 1-8, 2015.
[5] Z. Zhou, "HeadsUp: Keeping Pedestrian Phone Addicts from Dangers Using Mobile Phone Sensors," International Journal of Distributed Sensor Networks, vol. 2015, 2015.
[6] C. McGregor, B. Bonnis, B. Stanfield, and M. Stanfield, "A Method for Real-Time Stimulation and Response Monitoring Using Big Data and Its Application to Tactical Training," in Computer-Based Medical Systems (CBMS), 2015 IEEE 28th International Symposium on, 2015, pp. 169-170.
[7] K. M. Kapp, The gamification of learning and instruction: game-based methods and strategies for training and education: John Wiley & Sons, 2012.
[8] T. M. Fleming, C. Cheek, S. N. Merry, H. Thabrew, H. Bridgman, K. Stasiak, et al., "Serious games for the treatment or prevention of depression: a systematic review," Revista de Psicopatologia y Psicologia Clinica, vol. 19, pp. 227-242, 2014.
[9] G. N. Lewis and J. A. Rosie, "Virtual reality games for movement rehabilitation in neurological conditions: how do we meet the needs and expectations of the users?," Disability and rehabilitation, vol. 34, pp. 1880-1886, 2012.
[10] T. Vajk, P. Coulton, W. Bamford, and R. Edwards, "Using a mobile phone as a “Wii-like” controller for playing games on a large public display," International Journal of Computer Games Technology, vol. 2008, 2007.
[11] J. M. Silva and A. El Saddik, "Exertion interfaces for computer videogames using smartphones as input controllers," Multimedia systems, vol. 19, pp. 289-302, 2013.
[12] R. Meng, J. Isenhower, C. Qin, and S. Nelakuditi, "Can smartphone sensors enhance kinect experience?," in Proceedings of the thirteenth ACM international symposium on Mobile Ad Hoc Networking and Computing, 2012, pp. 265-266.
[13] "http://developer.android.com/guide/topics/sensors/sensors _overview.html", 2016.
[14] E. Bergamini, G. Ligorio, A. Summa, G. Vannozzi, A. Cappozzo, and A. M. Sabatini, "Estimating orientation using magnetic and inertial sensors and different sensor fusion approaches: accuracy assessment in manual and locomotion tasks," Sensors, vol. 14, pp. 18625-18649, 2014.
[15] S. O. Madgwick, A. J. Harrison, and R. Vaidyanathan, "Estimation of IMU and MARG orientation using a gradient descent algorithm," in Rehabilitation Robotics (ICORR), 2011 IEEE International Conference on, 2011, pp. 1-7.