An Occlusion Approach with Consistency Constraint for Multiscopic Depth Extraction

Niquin, Cédric; Prévost, Stéphanie; Rémion, Yannick

doi:10.1155/2010/857160

Cited by 13 publications

(5 citation statements)

References 18 publications

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“…Fig. 4 (d)-(f) present depth maps generated with the modified method of Niquin et al 24 Fig. 4 (g)-(i) show HDR images for the view 4/5 generated using the proposed method detailed in section 3 and after applying the Drago's tone mapping algorithm 30 with identical parameters.…”

Section: Resultsmentioning

confidence: 99%

High-dynamic range video acquisition with a multiview camera

et al. 2012

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We propose a new methodology to acquire HDR video content for autostereoscopic displays by adapting and augmenting an eight view video camera with standard sensors. To augment the intensity capacity of the sensors, we combine images taken at different exposures. Since the exposure has to be the same for all objectives of our camera, we fix the exposure variation by applying neutral density filters on each objective. Such an approach has two advantages: several exposures are known for each video frame and we do not need to worry about synchronization. For each pixel of each view, an HDR value is computed by a weighted average function applied to the values of matching pixels from all views. The building of the pixel match list is simplified by the property of our camera which has eight aligned, equally distributed objectives. At each frame, this results in an individual HDR image for each view while only one exposition per view was taken. The final eight HDR images are tone-mapped and interleaved for autostereoscopic display.

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Section: Resultsmentioning

confidence: 99%

High-dynamic range video acquisition with a multiview camera

et al. 2012

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“…The studied mSM method improves our previous one [31] while conserving its characteristics of directly multiscopic matching (altogether in every available image) ensuring the scene geometric consistency (depth maps coherence for each camera of the multiscopic unit) and encompassing occlusion detection. Furthermore, it's driven by a global optimization process that helps to avoid some outliers.…”

Section: Hints On Chosen Methodsmentioning

confidence: 99%

RECOVER3D: A Hybrid Multi-View System for 4D Reconstruction of Moving Actors

Lucas¹,

Souchet²,

Ismaël³

et al. 2013

Proceedings of the 4th International Conference on 3D Body Scanning Technologies, Long Beach CA, USA, 19-20 November 2013

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4D multi-view reconstruction of moving actors has many applications in the entertainment industry and although studios providing such services become more accessible, efforts have to be done in order to improve the underlying technology and to produce high-quality 3D contents. The RECOVER3D project aim is to elaborate an integrated virtual video system for the broadcast and motion pictures markets. In particular, we present a hybrid acquisition system coupling mono and multiscopic video cameras where actor's performance is captured as 4D data set: a sequence of 3D volumes over time. The visual improvement of the software solutions being implemented relies on "silhouette-based" techniques and (multi-)stereovision, following several hybridization scenarios integrating GPU-based processing. Afterwards, we transform this sequence of independent 3D volumes in a unique dynamic mesh. Our approach is based on a motion estimation procedure. An adaptive signed volume distance function is used as the principal shape descriptor and an optical flow algorithm is adapted to the surface setting with a modification that minimizes the interference between unrelated surface regions.

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“…Visibility: visibility reasoning evaluates for each target point with the function proposed by [2] and used in [18,19]. This function is defined in the framework as the product of non-materiality of potentially occluding samples (see [7] for more details about the visibility function formula).…”

Section: Main Framework Conceptsmentioning

confidence: 99%

Actor 3D reconstruction by a scene-based, visual hull guided, multi-stereovision framework

Ismaël¹,

Orozco²,

Loscos³

et al. 2018

CSRN

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This paper proposes a novel framework to produce 3D, high-precision models of humans from multi-view capture. This method's inputs are a visual hull and several sets of multi-baseline views. For each such view set, a surface is reconstructed with a multi-baseline stereovision method, then used to carve the visual hull. Carved visual hulls from different view sets are then fused pairwise to deliver the intended 3D model. The contributions of this paper are threefold: (i) the addition of visual hull guidance to a multi-baseline stereovision method, (ii) a carving solution to a visual hull from an interpolated and smooth stereovision surface, and (iii) a fusion solution to merge differently carved volumes differing in several areas. The paper shows that the proposed approach helps recovering a high quality carved volume, a 3D representation of the human to be modelled, that is precise even for small details and in concave areas subjected to occlusion.

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An Occlusion Approach with Consistency Constraint for Multiscopic Depth Extraction

Cited by 13 publications

References 18 publications

High-dynamic range video acquisition with a multiview camera

High-dynamic range video acquisition with a multiview camera

RECOVER3D: A Hybrid Multi-View System for 4D Reconstruction of Moving Actors

Actor 3D reconstruction by a scene-based, visual hull guided, multi-stereovision framework

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