A method for calculating the minimum number of cameras in a light field based free viewpoint video system

Shidanshidi, Hooman; Safaei, Farzad; Li, Wanqing

doi:10.1109/icme.2013.6607491

Cited by 8 publications

(15 citation statements)

References 16 publications

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“…In addition to LF system evaluation and comparison, by knowing the upper bound of the depth estimation error, optimum system parameters such as camera density , cameras resolution in terms of , and rendering complexity in terms of number of rays employed in interpolation |ω| can be theoretically calculated. For example, in [26], the authors have used the above relationships to obtain the minimum camera density for capturing a scene. We will show in future publications how ESD can be used to optimize the acquisition and rendering parameters of a LF system individually and jointly for a target output video quality.…”

Section: General Case Of Rendering Methods With Depth Mapsmentioning

confidence: 99%

“…This paper proposes a method to estimate the signal distortion that accounts for both acquisition and rendering. Specifically, this paper  extends the concept of effective sampling density (ESD) proposed by the authors in [25,26] and employs it as an indicator of signal distortion for a LF-based FVV system. Calculation of ESD requires neither a reference/ground truth nor the actual output images/video.…”

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confidence: 99%

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Estimation of Signal Distortion Using Effective Sampling Density for Light Field-Based Free Viewpoint Video

Shidanshidi

Safaei

2015

IEEE Trans. Multimedia

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In a light field-based free viewpoint video (LF-based FVV) system, effective sampling density (ESD) is defined as the number of rays per unit area of the scene that has been acquired and is selected in the rendering process for reconstructing an unknown ray. This paper extends the concept of ESD and shows that ESD is a tractable metric that quantifies the joint impact of the imperfections of LF acquisition and rendering. By deriving and analyzing ESD for the commonly used LF acquisition and rendering methods, it is shown that ESD is an effective indicator determined by system parameters and can be used to directly estimate output video distortion without access to the ground truth. This claim is verified by extensive numerical simulations and comparison to PSNR. Furthermore, an empirical relationship between the output distortion (in PSNR) and the calculated ESD is established to allow direct assessment of the overall video distortion without an actual implementation of the system. A small scale subjective user study is also conducted which indicates a correlation of 0.91 between ESD and perceived quality. (ESD) is defined as the number of rays per unit area of the scene that has been acquired and is selected in the rendering process for reconstructing an unknown ray. This paper extends the concept of ESD and shows that ESD is a tractable metric that quantifies the joint impact of the imperfections of LF acquisition and rendering. By deriving and analyzing ESD for the commonly used LF acquisition and rendering methods, it is shown that ESD is an effective indicator determined by system parameters and can be used to directly estimate output video distortion without access to the ground truth. This claim is verified by extensive numerical simulations and comparison to PSNR. Furthermore, an empirical relationship between the output distortion (in PSNR) and the calculated ESD is established to allow direct assessment of the overall video distortion without an actual implementation of the system. A small scale subjective user study is also conducted which indicates a correlation of 0.91 between ESD and perceived quality.

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Section: General Case Of Rendering Methods With Depth Mapsmentioning

confidence: 99%

mentioning

confidence: 99%

Estimation of Signal Distortion Using Effective Sampling Density for Light Field-Based Free Viewpoint Video

Shidanshidi

Safaei

2015

IEEE Trans. Multimedia

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“…Although numerous single-camera models exist (surveyed in [8,9,10]), there are few models describing multi-camera systems [3,11,12,13,14,15,16]. These models describe the spatial relations between cameras, but do not treat camera synchronization error (desynchronization) as a system parameter affecting depth uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Modeling depth uncertainty of desynchronized multi-camera systems

Dima

Sjöström

Olsson

2017

2017 International Conference on 3D Immersion (IC3D)

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Accurately recording motion from multiple perspectives is relevant for recording and processing immersive multi-media and virtual reality content. However, synchronization errors between multiple cameras limit the precision of scene depth reconstruction and rendering. In order to quantify this limit, a relation between camera de-synchronization, camera parameters, and scene element motion has to be identified. In this paper, a parametric ray model describing depth uncertainty is derived and adapted for the pinhole camera model. A two-camera scenario is simulated to investigate the model behavior and how camera synchronization delay, scene element speed, and camera positions affect the system's depth uncertainty. Results reveal a linear relation between synchronization error, element speed, and depth uncertainty. View convergence is shown to affect mean depth uncertainty up to a factor of 10. Results also show that depth uncertainty must be assessed on the full set of camera rays instead of a central subset.

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“…ESD is defined as the number of rays per unit area of the scene that have been captured by acquisition component and chosen by ray selection process to be employed in the rendering. Not surprisingly, it has been shown that ESD is the true indicator of output quality, not SD ─ except that ESD is fundamentally bound by SD [11,12]. In addition, ESD provides an analytically tractable way for evaluating the influence of the imperfections of both acquisition and rendering components on output quality.…”

Section: Introductionmentioning

confidence: 99%

Optimization of the number of rays in interpolation for light field based free viewpoint systems

Shidanshidi

Safaei

2015

2015 IEEE International Conference on Multimedia and Expo (ICME)

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Light field (LF) rendering is widely used in free viewpoint video systems (FVV). Different methods have been proposed to employ depth maps to improve the rendering quality. However, estimation of depth is often error-prone. In this paper, a new method based on the concept of effective sampling density (ESD) is proposed for evaluating the depth-based LF rendering algorithms at different levels of errors in the depth estimation. In addition, for a given rendering quality, we provide an estimation of number of rays required in the interpolation algorithm to compensate for the adverse effect caused by errors in depth maps. The proposed method is particularly useful in designing a rendering algorithm with inaccurate knowledge of depth to achieve the required rendering quality. Both the theoretical study and numerical simulations have verified the efficacy of the proposed method. OPTIMIZATION OF THE NUMBER OF RAYS IN INTERPOLATION FOR LIGHT FIELD BASED FREE VIEWPOINT SYSTEMS Hooman Shidanshidi, Farzad Safaei, Wanqing LiICT Research Institute, University of Wollongong, Australia hooman@uow.edu.au, farzad@uow.edu, wanqing@uow.edu.au ABSTRACT Light field (LF) rendering is widely used in free viewpoint video systems (FVV). Different methods have been proposed to employ depth maps to improve the rendering quality. However, estimation of depth is often error-prone. In this paper, a new method based on the concept of effective sampling density (ESD) is proposed for evaluating the depth-based LF rendering algorithms at different levels of errors in the depth estimation. In addition, for a given rendering quality, we provide an estimation of number of rays required in the interpolation algorithm to compensate for the adverse effect caused by errors in depth maps. The proposed method is particularly useful in designing a rendering algorithm with inaccurate knowledge of depth to achieve the required rendering quality. Both the theoretical study and numerical simulations have verified the efficacy of the proposed method.

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A method for calculating the minimum number of cameras in a light field based free viewpoint video system

Cited by 8 publications

References 16 publications

Estimation of Signal Distortion Using Effective Sampling Density for Light Field-Based Free Viewpoint Video

Estimation of Signal Distortion Using Effective Sampling Density for Light Field-Based Free Viewpoint Video

Modeling depth uncertainty of desynchronized multi-camera systems

Optimization of the number of rays in interpolation for light field based free viewpoint systems

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