Camera pose estimation of a smartphone at a field without interest points

Ruiko Miyano, Takuya Inoue, Takuya Minagawa, Yuko Uematsu, Hideo Saito

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

An Augmented Reality (AR) system on mobile phones has recently attracted attention because smartphones have increasingly been popular. For an AR system, we have to know a camera pose of a smartphone. A sensor-based method is one of the most popular ways to estimate the camera pose, but it cannot estimate an accurate pose. A vision-based method is another way to estimate the camera pose, but it is not suitable to a scene with few interest points such as a sports field. In this paper, we propose a novel method of a camera pose estimation for a scene without interest points by combining a sensor-based and a vision-based approach. In our proposed method, we use an acceleration and a magnetic sensor to roughly estimate a camera pose, then search the accurate pose by matching a captured image with a set of reference images. Our experiments show that our proposed method is accurate and fast enough to apply a real-time AR system.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages545-555
Number of pages11
Volume7729 LNCS
EditionPART 2
DOIs
Publication statusPublished - 2013
Event11th Asian Conference on Computer Vision, ACCV 2012 - Daejeon, Korea, Republic of
Duration: 2012 Nov 52012 Nov 6

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7729 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other11th Asian Conference on Computer Vision, ACCV 2012
CountryKorea, Republic of
CityDaejeon
Period12/11/512/11/6

Fingerprint

Pose Estimation
Smartphones
Camera
Cameras
Augmented reality
Augmented Reality
Sensor
Estimate
Magnetic sensors
Sensors
Mobile Phone
Sports
Mobile phones
Real-time
Experiment
Experiments

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Miyano, R., Inoue, T., Minagawa, T., Uematsu, Y., & Saito, H. (2013). Camera pose estimation of a smartphone at a field without interest points. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 2 ed., Vol. 7729 LNCS, pp. 545-555). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7729 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-37484-5_44

Camera pose estimation of a smartphone at a field without interest points. / Miyano, Ruiko; Inoue, Takuya; Minagawa, Takuya; Uematsu, Yuko; Saito, Hideo.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7729 LNCS PART 2. ed. 2013. p. 545-555 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7729 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Miyano, R, Inoue, T, Minagawa, T, Uematsu, Y & Saito, H 2013, Camera pose estimation of a smartphone at a field without interest points. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 2 edn, vol. 7729 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 7729 LNCS, pp. 545-555, 11th Asian Conference on Computer Vision, ACCV 2012, Daejeon, Korea, Republic of, 12/11/5. https://doi.org/10.1007/978-3-642-37484-5_44
Miyano R, Inoue T, Minagawa T, Uematsu Y, Saito H. Camera pose estimation of a smartphone at a field without interest points. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 2 ed. Vol. 7729 LNCS. 2013. p. 545-555. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). https://doi.org/10.1007/978-3-642-37484-5_44
Miyano, Ruiko ; Inoue, Takuya ; Minagawa, Takuya ; Uematsu, Yuko ; Saito, Hideo. / Camera pose estimation of a smartphone at a field without interest points. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7729 LNCS PART 2. ed. 2013. pp. 545-555 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).
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