Pixel Reprojection of 360 Degree Renderings for Small Parallax Effects

Lecture Notes in Computer Science - Augmented Reality, Virtual Reality, and Computer Graphics ◽

10.1007/978-3-319-60922-5_19 ◽

2017 ◽

pp. 253-262

Author(s):

Joakim Bruslund Haurum ◽

Christian Nygaard Daugbjerg ◽

Péter Rohoska ◽

Andrea Coifman ◽

Anne Juhler Hansen ◽

...

Keyword(s):

Parallax Effects

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Digital 3D, Parallax Effects, and the Construction of Film Space in Tangled 3D and Cave of Forgotten Dreams 3D

Screen Space Reconfigured ◽

10.5117/9789089649928_ch03 ◽

2020 ◽

Author(s):

Kristen Whissel

Keyword(s):

Case Studies ◽

Ideal Case ◽

Moving Image ◽

The Past ◽

Parallax Effects

This essay analyzes how parallax effects in Cave of Forgotten Dreams 3D (2010) and Tangled 3D (2010) effectively blur the boundaries between the past and present, sight and touch, and diegetic space and the space of reception in order to give form to themes concerning the dimensionality of the moving image. I show how these films function as ideal case studies for demonstrating digital 3D’s transformation of film space by organizing seeing, knowing, and feeling along the screen’s z-axis.

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Position determination and strong field parallax effects for photon emitters in the Schwarzschild spacetime

General Relativity and Gravitation ◽

10.1007/s10714-017-2318-4 ◽

2017 ◽

Vol 49 (12) ◽

Cited By ~ 1

Author(s):

Donato Bini ◽

Andrea Geralico ◽

Robert T. Jantzen

Keyword(s):

Strong Field ◽

Schwarzschild Spacetime ◽

Position Determination ◽

Parallax Effects

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Accurate estimation of fish length in single camera photogrammetry with a fiducial marker

ICES Journal of Marine Science ◽

10.1093/icesjms/fsz030 ◽

2019 ◽

Vol 77 (6) ◽

pp. 2245-2254 ◽

Cited By ~ 3

Author(s):

Graham G Monkman ◽

Kieran Hyder ◽

Michel J Kaiser ◽

Franck P Vidal

Keyword(s):

Data Collection ◽

Image Distortion ◽

Fiducial Marker ◽

Mean Bias Error ◽

Accurate Estimation ◽

Bias Error ◽

Fish Length ◽

Estimation Errors ◽

Camera Systems ◽

Parallax Effects

Abstract Videogrammetry and photogrammetry are increasingly being used in marine science for unsupervised data collection. The camera systems employed are complex, in contrast to “consumer” digital cameras and smartphones carried by potential citizen scientists. However, using consumer cameras in photogrammetry will introduce unknown length estimation errors through both the image acquisition process and lens distortion. This study presents a methodology to achieve accurate 2-dimensional (2-D) total length (TL) estimates of fish without specialist equipment or proprietary software. Photographs of fish were captured with an action camera using a background fiducial marker, a foreground fiducial marker and a laser marker. The geometric properties of the lens were modelled with OpenCV to correct image distortion. TL estimates were corrected for parallax effects using an algorithm requiring only the initial length estimate and known fish morphometric relationships. Correcting image distortion decreased RMSE by 96% and the percentage mean bias error (%MBE) by 50%. Correcting for parallax effects achieved a %MBE of −0.6%. This study demonstrates that the morphometric measurement of different species can be accurately estimated without the need for complex camera equipment, making it particularly suitable for deployment in citizen science and other volunteer-based data collection endeavours.

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