Graphics Reference
In-Depth Information
Figure 1.6
The high-resolution and real-time 3D shape measurement system proposed by Zhang and
Yau (2007) is based on the modified 2
+
1 phase-shifting algorithm and particularly adapted for face
acquisition. The data acquisition speed is as high as 60 frames per second while the image resolution is
640
×
480 pixels per frame. Here a photograph captured during the experiment is illustrated. The left
side of the image shows the subject, whereas the right side shows the real-time reconstructed geometry
A robust phase unwrapping approach called “multilevel quality-guided phase unwrapping
algorithm” is also proposed in Zhang et al. (2007).
Ouji et al. (2011) proposed a cost-effective 3D video acquisition solution with a 3D super-
resolution scheme, using three calibrated cameras coupled with a non-calibrated projector
device, which is particularly suited to 3D face scanning, that is, rapid, easily movable, and
robust to ambient lighting conditions. Their solution is a hybrid stereovision and phase-
shifting approach that not only takes advantage of the assets of stereovision and structured
light but also overcomes their weaknesses. First, a 3D sparse model is estimated from stereo
matching with a fringe-based resolution and a sub-pixel precision. Then projector parameters
are automatically estimated through an inline stage. A dense 3D model is recovered by the
intrafringe phase estimation, from the two sinusoidal fringe images and a texture image,
independently from the left, middle, and right cameras. Finally, the left, middle, and right
3D dense models are fused to produce the final 3D model, which constitutes a spatial
super-resolution. In contrast with previous methods, camera-projector calibration and phase-
unwrapping stages are avoided.
1.3.3 Multiview Static Reconstruction
The aim of multiview stereo (MVS) reconstruction is twofold. Firstly, it allows to reinforce con-
straints on stereo matching, discard false matches, and increase the precision of good matches.
Secondly, spatial arrangement of cameras allows covering the entire face. To reduce the com-
plexity, as well as achieve high quality reconstruction, multiview reconstruction approaches
usually proceed in a coarse-to-fine sequence. Finally, multiview approaches involve high res-
olution images captured in real time, whereas the processing stage requires tens of minutes.
MVS scene and object reconstruction approaches can be organized into four categories. The
first category operates first by estimating a cost function on a 3D volume and then extracting
