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

Результат исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференции

Выдержка

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.

Язык оригиналаанглийский
Название основной публикацииComputational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings
РедакторыBeniamino Murgante, Osvaldo Gervasi, Elena Stankova, Vladimir Korkhov, Sanjay Misra, Carmelo Torre, Eufemia Tarantino, David Taniar, Ana Maria A.C. Rocha, Bernady O. Apduhan
ИздательSpringer
Страницы772-781
Число страниц10
ISBN (печатное издание)9783030243043
DOI
СостояниеОпубликовано - 29 июн 2019
Событие19th International Conference on Computational Science and Its Applications, ICCSA 2019 - Saint Petersburg, Российская Федерация
Продолжительность: 1 июл 20194 июл 2019

Серия публикаций

НазваниеLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Том11622 LNCS
ISSN (печатное издание)0302-9743
ISSN (электронное издание)1611-3349

Конференция

Конференция19th International Conference on Computational Science and Its Applications, ICCSA 2019
СтранаРоссийская Федерация
ГородSaint Petersburg
Период1/07/194/07/19

Отпечаток

Camera
Cameras
Augmented reality
Printed circuit boards
Necessary
Hardware Architecture
Augmented Reality
Tracking System
Software Architecture
Pi
Infrared radiation
Neural networks
Hardware
Neural Network Model
Sensors
Infrared
Strictly
Industry
Filter
Costs

Предметные области Scopus

  • Теоретические компьютерные науки
  • Компьютерные науки (все)

Цитировать

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. В B. Murgante, O. Gervasi, E. Stankova, V. Korkhov, S. Misra, C. Torre, E. Tarantino, D. Taniar, A. M. A. C. Rocha, ... B. O. Apduhan (Ред.), Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings (стр. 772-781). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 11622 LNCS). Springer. https://doi.org/10.1007/978-3-030-24305-0_58
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. редактор / 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, 2019. стр. 772-781 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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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.",
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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. в B Murgante, O Gervasi, E Stankova, V Korkhov, S Misra, C Torre, E Tarantino, D Taniar, AMAC Rocha & BO Apduhan (ред.), 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), том. 11622 LNCS, Springer, стр. 772-781, Saint Petersburg, Российская Федерация, 1/07/19. https://doi.org/10.1007/978-3-030-24305-0_58

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. ред. / 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, 2019. стр. 772-781 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 11622 LNCS).

Результат исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференции

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.

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

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

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

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

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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

ER -

Oleg I, Sevostyanov R, Degtyarev A, Karpiy PE, Kuzevanova EG, Kitaeva AA и соавт. Position Tracking in 3D Space Based on a Data of a Single Camera. В Murgante B, Gervasi O, Stankova E, Korkhov V, Misra S, Torre C, Tarantino E, Taniar D, Rocha AMAC, Apduhan BO, редакторы, Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings. Springer. 2019. стр. 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