High-Resolution, Real-time 3D Shape Acquisition

Zhang, Song; Huang, Peisen S.

doi:10.1109/cvpr.2004.360

Cited by 77 publications

(6 citation statements)

References 22 publications

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“…The computational workload is therefore significantly lower compared to our system with statistical patterns. For instance, Zhang and Huang [36] reported a computation time of 24.2 ms for the 3D-reconstruction of a scene with 532 × 500 pixels on a PC in the year 2004.…”

Section: Comparison With Other Methodsmentioning

confidence: 99%

BICOS—An Algorithm for Fast Real-Time Correspondence Search for Statistical Pattern Projection-Based Active Stereo Sensors

et al. 2019

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Pattern projection-based 3D measurement systems are widely used for contactless, non-destructive optical 3D shape measurements. In addition, many robot-operated automation tasks require real-time reconstruction of accurate 3D data. In previous works, we have demonstrated 3D scanning based on statistical pattern projection-aided stereo matching between two cameras. One major advantage of this technology is that the actually projected patterns do not have to be known a priori in the reconstruction software. This allows much simpler projector designs and enables high-speed projection. However, to find corresponding pixels between cameras, it is necessary to search the best match amongst all pixels within the geometrically possible image area (that is, within a range on the corresponding epipolar line). The well-established method for this search is to compare each candidate pixel by temporal normalized cross correlation of the brightness value sequences of both pixels. This is computationally expensive and interdicts fast real-time applications on inexpensive computer hardware. We show two variants of our algorithm “Binary Correspondence Search” (BICOS), which solve this task in significantly reduced calculation time. In practice, our algorithm is much faster than traditional, purely cross-correlation-based search while maintaining a similar level of accuracy.

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Section: Comparison With Other Methodsmentioning

confidence: 99%

BICOS—An Algorithm for Fast Real-Time Correspondence Search for Statistical Pattern Projection-Based Active Stereo Sensors

et al. 2019

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“…wrinkles and folds). All these methods involve highly specialized sensors and/or controlled studio environments [Zhang and Huang 2004;Borshukov et al 2005;Ma et al 2007;Beeler et al 2010;Bradley et al 2010]. High-resolution facial motion is generally recovered through variants of non-rigid registration and tracking algorithms across sequences of input geometry, texture, or both Furukawa and Ponce 2009;Alexander et al 2009;Li et al 2009;Weise et al 2009;Bradley et al 2010;Wilson et al 2010].…”

Section: Related Workmentioning

confidence: 99%

Realtime performance-based facial animation

Weise

Bouaziz

et al. 2011

ACM SIGGRAPH 2011 Papers

261

201

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“…Moreover, correspondences are not stably determined, because the patterns are distorted because of the colour and the shapes of the object surface. Many methods have been proposed to solve the problems; for example, using multiple stripes with globally unique colour combinations [16, 17], dotted lines with unique modulations of the dots [18, 19], 2D area information for encoding [1, 20], or connections of grid patterns [7, 9, 21, 22]. However, no method has achieved a sufficient performance in all aspects of precision, resolution and stability.…”

Section: Related Workmentioning

confidence: 99%

Single colour one‐shot scan using modified Penrose tiling pattern

Kawasaki

Masuyama

Sagawa

et al. 2013

IET Computer Vision

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In this paper, we propose a new technique to achieve one-shot scan using single color and static pattern projector; such a method is ideal for acquisition of moving objects. Since projector-camera systems generally have uncertainties on retrieving correspondences between the captured image and the projected pattern, many solutions have been proposed. Especially for one-shot scan, which means that only a single image is required for shape reconstruction, positional information of a pixel of the projected pattern should be encoded by spatial and/or color information. Although color information is frequently used for encoding, it is severely affected by texture and material of the object and leads unstable reconstruction. In this paper, we propose a technique to solve the problem by using geometrically unique pattern only with black and white color which further considers the shape distortion by surface orientation of the shape. Our technique successfully acquires high precision one-shot scan with an actual system.

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High-Resolution, Real-time 3D Shape Acquisition

Cited by 77 publications

References 22 publications

BICOS—An Algorithm for Fast Real-Time Correspondence Search for Statistical Pattern Projection-Based Active Stereo Sensors

BICOS—An Algorithm for Fast Real-Time Correspondence Search for Statistical Pattern Projection-Based Active Stereo Sensors

Realtime performance-based facial animation

Single colour one‐shot scan using modified Penrose tiling pattern

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