Predicting head trajectories in 360° virtual reality videos

A. Deniz Aladagli, Erhan Ekmekcioglu, Dmitri Jarnikov, Ahmet Kondoz

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

5 Citations (Scopus)

Abstract

In this paper a fixation prediction based saliency algorithm is used in order to predict the head movements of viewers watching virtual reality (VR) videos, by modelling the relationship between fixation predictions and recorded head movements. The saliency algorithm is applied to viewings faithfully recreated from recorded head movements. Spherical cross-correlation analysis is performed between predicted attention centres and actual viewing centres in order to try and identify prevalent lengths of predictable attention and how early they can be predicted. The results show that fixation prediction based saliency analysis correlates with head movements only for limited durations. Therefore, further classification of durations where saliency analysis is predictive is required.

LanguageEnglish
Title of host publication2017 International Conference on 3D Immersion, IC3D 2017 - Proceedings
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages1-6
Number of pages6
ISBN (Electronic)9781538646557
DOIs
StatePublished - 8 Jan 2018
Event7th International Conference on 3D Immersion (IC3D 2017) - Brussels, Belgium
Duration: 11 Dec 201712 Dec 2017
Conference number: 7

Conference

Conference7th International Conference on 3D Immersion (IC3D 2017)
Abbreviated titleIC3D 2017
CountryBelgium
CityBrussels
Period11/12/1712/12/17

Fingerprint

Virtual reality
Trajectories
Predictive analytics

Keywords

  • 360, VR
  • head
  • omnidirectional
  • prediction
  • saliency
  • video

Cite this

Aladagli, A. D., Ekmekcioglu, E., Jarnikov, D., & Kondoz, A. (2018). Predicting head trajectories in 360° virtual reality videos. In 2017 International Conference on 3D Immersion, IC3D 2017 - Proceedings (pp. 1-6). Piscataway: Institute of Electrical and Electronics Engineers. DOI: 10.1109/IC3D.2017.8251913
Aladagli, A. Deniz ; Ekmekcioglu, Erhan ; Jarnikov, Dmitri ; Kondoz, Ahmet. / Predicting head trajectories in 360° virtual reality videos. 2017 International Conference on 3D Immersion, IC3D 2017 - Proceedings. Piscataway : Institute of Electrical and Electronics Engineers, 2018. pp. 1-6
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Aladagli, AD, Ekmekcioglu, E, Jarnikov, D & Kondoz, A 2018, Predicting head trajectories in 360° virtual reality videos. in 2017 International Conference on 3D Immersion, IC3D 2017 - Proceedings. Institute of Electrical and Electronics Engineers, Piscataway, pp. 1-6, 7th International Conference on 3D Immersion (IC3D 2017), Brussels, Belgium, 11/12/17. DOI: 10.1109/IC3D.2017.8251913

Predicting head trajectories in 360° virtual reality videos. / Aladagli, A. Deniz; Ekmekcioglu, Erhan; Jarnikov, Dmitri; Kondoz, Ahmet.

2017 International Conference on 3D Immersion, IC3D 2017 - Proceedings. Piscataway : Institute of Electrical and Electronics Engineers, 2018. p. 1-6.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - Predicting head trajectories in 360° virtual reality videos

AU - Aladagli,A. Deniz

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AU - Jarnikov,Dmitri

AU - Kondoz,Ahmet

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Y1 - 2018/1/8

N2 - In this paper a fixation prediction based saliency algorithm is used in order to predict the head movements of viewers watching virtual reality (VR) videos, by modelling the relationship between fixation predictions and recorded head movements. The saliency algorithm is applied to viewings faithfully recreated from recorded head movements. Spherical cross-correlation analysis is performed between predicted attention centres and actual viewing centres in order to try and identify prevalent lengths of predictable attention and how early they can be predicted. The results show that fixation prediction based saliency analysis correlates with head movements only for limited durations. Therefore, further classification of durations where saliency analysis is predictive is required.

AB - In this paper a fixation prediction based saliency algorithm is used in order to predict the head movements of viewers watching virtual reality (VR) videos, by modelling the relationship between fixation predictions and recorded head movements. The saliency algorithm is applied to viewings faithfully recreated from recorded head movements. Spherical cross-correlation analysis is performed between predicted attention centres and actual viewing centres in order to try and identify prevalent lengths of predictable attention and how early they can be predicted. The results show that fixation prediction based saliency analysis correlates with head movements only for limited durations. Therefore, further classification of durations where saliency analysis is predictive is required.

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Aladagli AD, Ekmekcioglu E, Jarnikov D, Kondoz A. Predicting head trajectories in 360° virtual reality videos. In 2017 International Conference on 3D Immersion, IC3D 2017 - Proceedings. Piscataway: Institute of Electrical and Electronics Engineers. 2018. p. 1-6. Available from, DOI: 10.1109/IC3D.2017.8251913