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Position Tracking in 3D Space Based on a Data of a Single Camera. / Oleg, Iakushkin; Sevostyanov, Ruslan; Degtyarev, Alexander; Karpiy, P. E.; Kuzevanova, E. G.; Kitaeva, A. A.; Sergiev, S. A.

Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings. ed. / Beniamino Murgante; Osvaldo Gervasi; Elena Stankova; Vladimir Korkhov; Sanjay Misra; Carmelo Torre; Eufemia Tarantino; David Taniar; Ana Maria A.C. Rocha; Bernady O. Apduhan. Springer Nature, 2019. p. 772-781 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11622 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Oleg, I, Sevostyanov, R, Degtyarev, A, Karpiy, PE, Kuzevanova, EG, Kitaeva, AA & Sergiev, SA 2019, Position Tracking in 3D Space Based on a Data of a Single Camera. in B Murgante, O Gervasi, E Stankova, V Korkhov, S Misra, C Torre, E Tarantino, D Taniar, AMAC Rocha & BO Apduhan (eds), Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11622 LNCS, Springer Nature, pp. 772-781, 19th International Conference on Computational Science and Its Applications, ICCSA 2019, Saint Petersburg, Russian Federation, 1/07/19. https://doi.org/10.1007/978-3-030-24305-0_58

APA

Oleg, I., Sevostyanov, R., Degtyarev, A., Karpiy, P. E., Kuzevanova, E. G., Kitaeva, A. A., & Sergiev, S. A. (2019). Position Tracking in 3D Space Based on a Data of a Single Camera. In B. Murgante, O. Gervasi, E. Stankova, V. Korkhov, S. Misra, C. Torre, E. Tarantino, D. Taniar, A. M. A. C. Rocha, & B. O. Apduhan (Eds.), Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings (pp. 772-781). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11622 LNCS). Springer Nature. https://doi.org/10.1007/978-3-030-24305-0_58

Vancouver

Oleg I, Sevostyanov R, Degtyarev A, Karpiy PE, Kuzevanova EG, Kitaeva AA et al. Position Tracking in 3D Space Based on a Data of a Single Camera. In Murgante B, Gervasi O, Stankova E, Korkhov V, Misra S, Torre C, Tarantino E, Taniar D, Rocha AMAC, Apduhan BO, editors, Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings. Springer Nature. 2019. p. 772-781. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-24305-0_58

Author

Oleg, Iakushkin ; Sevostyanov, Ruslan ; Degtyarev, Alexander ; Karpiy, P. E. ; Kuzevanova, E. G. ; Kitaeva, A. A. ; Sergiev, S. A. / Position Tracking in 3D Space Based on a Data of a Single Camera. Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings. editor / Beniamino Murgante ; Osvaldo Gervasi ; Elena Stankova ; Vladimir Korkhov ; Sanjay Misra ; Carmelo Torre ; Eufemia Tarantino ; David Taniar ; Ana Maria A.C. Rocha ; Bernady O. Apduhan. Springer Nature, 2019. pp. 772-781 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{c3efd2de14aa4d499a507c85675d29fb,
title = "Position Tracking in 3D Space Based on a Data of a Single Camera",
abstract = "A high cost of equipment that solves the problem of tracking the position and direction of users in real time is one of factors that negatively affect the speed of development of the augmented reality industry. The urgency of this problem is a premise for the development of a financially available tracking system. In this research, we propose a software and hardware architecture of a system that solves three-dimensional tracking problems in a closed space and postures classification using neural network models. Distinctive feature of our system is the feasibility in borders of strictly limited computing power and the absence of any sensors placed on monitored objects. After setting the boundaries of the active area, all the necessary input data is provided by a static camera without an infrared filter. As an example of the implementation of a resource-limited solution, we present the assembly of this solution on a Raspberry Pi version 3 single board computer equipped with the Intel Neural Stick version 2 co-processor and a Raspberry version 2 NoIR camera. The first section of the article describes technical characteristics of the equipment used in the study. The second part is dedicated to the solution algorithm and its brief description. Further, in the third stage, the ways of data collection, necessary for a correct assessment of position, direction and posture are illustrated. The fourth, final section presents the results, discussion and possible directions for further work.",
keywords = "Augmented reality, Internet of things, Optical flow, Software",
author = "Iakushkin Oleg and Ruslan Sevostyanov and Alexander Degtyarev and Karpiy, {P. E.} and Kuzevanova, {E. G.} and Kitaeva, {A. A.} and Sergiev, {S. A.}",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 19th International Conference on Computational Science and Its Applications, ICCSA 2019 ; Conference date: 01-07-2019 Through 04-07-2019",
year = "2019",
month = jun,
day = "29",
doi = "10.1007/978-3-030-24305-0_58",
language = "English",
isbn = "9783030243043",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "772--781",
editor = "Beniamino Murgante and Osvaldo Gervasi and Elena Stankova and Vladimir Korkhov and Sanjay Misra and Carmelo Torre and Eufemia Tarantino and David Taniar and Rocha, {Ana Maria A.C.} and Apduhan, {Bernady O.}",
booktitle = "Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings",
address = "Germany",

}

RIS

TY - GEN

T1 - Position Tracking in 3D Space Based on a Data of a Single Camera

AU - Oleg, Iakushkin

AU - Sevostyanov, Ruslan

AU - Degtyarev, Alexander

AU - Karpiy, P. E.

AU - Kuzevanova, E. G.

AU - Kitaeva, A. A.

AU - Sergiev, S. A.

N1 - Conference code: 19

PY - 2019/6/29

Y1 - 2019/6/29

N2 - A high cost of equipment that solves the problem of tracking the position and direction of users in real time is one of factors that negatively affect the speed of development of the augmented reality industry. The urgency of this problem is a premise for the development of a financially available tracking system. In this research, we propose a software and hardware architecture of a system that solves three-dimensional tracking problems in a closed space and postures classification using neural network models. Distinctive feature of our system is the feasibility in borders of strictly limited computing power and the absence of any sensors placed on monitored objects. After setting the boundaries of the active area, all the necessary input data is provided by a static camera without an infrared filter. As an example of the implementation of a resource-limited solution, we present the assembly of this solution on a Raspberry Pi version 3 single board computer equipped with the Intel Neural Stick version 2 co-processor and a Raspberry version 2 NoIR camera. The first section of the article describes technical characteristics of the equipment used in the study. The second part is dedicated to the solution algorithm and its brief description. Further, in the third stage, the ways of data collection, necessary for a correct assessment of position, direction and posture are illustrated. The fourth, final section presents the results, discussion and possible directions for further work.

AB - A high cost of equipment that solves the problem of tracking the position and direction of users in real time is one of factors that negatively affect the speed of development of the augmented reality industry. The urgency of this problem is a premise for the development of a financially available tracking system. In this research, we propose a software and hardware architecture of a system that solves three-dimensional tracking problems in a closed space and postures classification using neural network models. Distinctive feature of our system is the feasibility in borders of strictly limited computing power and the absence of any sensors placed on monitored objects. After setting the boundaries of the active area, all the necessary input data is provided by a static camera without an infrared filter. As an example of the implementation of a resource-limited solution, we present the assembly of this solution on a Raspberry Pi version 3 single board computer equipped with the Intel Neural Stick version 2 co-processor and a Raspberry version 2 NoIR camera. The first section of the article describes technical characteristics of the equipment used in the study. The second part is dedicated to the solution algorithm and its brief description. Further, in the third stage, the ways of data collection, necessary for a correct assessment of position, direction and posture are illustrated. The fourth, final section presents the results, discussion and possible directions for further work.

KW - Augmented reality

KW - Internet of things

KW - Optical flow

KW - Software

UR - http://www.scopus.com/inward/record.url?scp=85068614268&partnerID=8YFLogxK

UR - http://www.mendeley.com/research/position-tracking-3d-space-based-data-single-camera

U2 - 10.1007/978-3-030-24305-0_58

DO - 10.1007/978-3-030-24305-0_58

M3 - Conference contribution

AN - SCOPUS:85068614268

SN - 9783030243043

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 772

EP - 781

BT - Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings

A2 - Murgante, Beniamino

A2 - Gervasi, Osvaldo

A2 - Stankova, Elena

A2 - Korkhov, Vladimir

A2 - Misra, Sanjay

A2 - Torre, Carmelo

A2 - Tarantino, Eufemia

A2 - Taniar, David

A2 - Rocha, Ana Maria A.C.

A2 - Apduhan, Bernady O.

PB - Springer Nature

T2 - 19th International Conference on Computational Science and Its Applications, ICCSA 2019

Y2 - 1 July 2019 through 4 July 2019

ER -

ID: 43696607