### Table 1. Ambiguity in reconstruction of symmetric curves: A single view is not enough for re- construction of general symmetric curves, except for case (a) of Figure 2, but sufficient for planar symmetric curves. Two or more views are needed for reconstruction of generally shaped sym- metric curves.

2004

"... In PAGE 8: ... For curves with general shapes, the solution is always unique. To conclude Section 3, we summarize all cases of symmetric curves studied so far in Table1 , in terms of ambiguities in reconstruction from one or two views. 8 We have also tried other distances such as L1-distance and C1-distance.... ..."

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### Table 1 Reconstruction error per DOF (in normalized coordinates) Data used 3D reconstruction error

"... In PAGE 12: ...ut the x locations were not. Fig. 7 shows the coordinates used and a sample reconstruction for this experiment. Note that in both cases (see Table1 ), the re- construction is quite accurate in terms of mean- squared error. This shows that the ten learned modes are a su ciently strong characterization to accurately reconstruct the 3D lip shape from 2D data.... ..."

### Table 1. The shapes and the boundary parametrizations of the obstacles reconstructed.

"... In PAGE 23: ... The obstacles reconstructed were of various shapes and oriented variously with respect to the directions of incidence. Table1 describes the geometries and the parametrizations of the scatterers. All reconstructions were obtained from the far-field data and for more than one frequency and direction of incidence.... ..."

### Table 2. The comparison of 3D reconstruction measurement data of a resistance. NURBS curves MDP

2006

"... In PAGE 6: ... Detailed comparison of matching results obtained with these methods is given in table 1. Table2 gives a comparison of 3D measurement results of the resistance. 6.... ..."

### Table 5.4: Peak shape point error in the reconstructed shape. The percentage error is given with respect to the perimeter of the bounding box of plan views, and with respect to the diagonal of the 3D bounding box of shape points.

### Table 2 : Error chart, rigid body model vs. multiple un- calibrated camera 3D reconstruction, real data. The root mean square 3D reconstruction error per marker per time step for the Spoor amp; Veldpas rigid body technique com- pared to the homogeneous factorization technique for the actual data sequence of the face. As the number of basis shapes is increased the error decreases.

"... In PAGE 10: ... 3.3 3D Reconstruction from Multiple uncalibrated cameras Table2 shows the multiple uncalibrated camera recon- struction errors for a video sequence of a face rotating and deforming. This reconstruction is the most challeng- ing task, since it tests the entire system from video input to 3D output.... ..."

### Table 2: 3D point reconstruction error for the RADIUS image data.

2000

"... In PAGE 24: ... Our algorithm recovered 61 correspondence rooftop polygon points, all of them correct (Figures 11 and 12). The corresponding 3D points reconstructed by the al- gorithm are reported in Table2 . This experiment uses the ground truth 3D data supplied in the model board 1 data set Here we only reported the comparisons between the reconstructed 3D points and their ground truth data for those 3D points whose ground truth coordinates are available.... In PAGE 24: ... This experiment uses the ground truth 3D data supplied in the model board 1 data set Here we only reported the comparisons between the reconstructed 3D points and their ground truth data for those 3D points whose ground truth coordinates are available. From Table2 , we can see that for some image correspondences such as 20, 21, 34, 35, 36, 49, 50, and 57, the trian- gulated 3D points have large errors although their correspondences are determined correctly by our algorithm. This is due mainly to the errors in the locations of rooftop polygon points, since it is well known that these 2D errors have a significant effect on the triangulated 3D data, especially when there are only two images [17].... ..."

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### Table 3: Baseline accuracy of the 3D reconstruction pro-

1996

"... In PAGE 6: ... The accuracy of each reconstructed roof polygon was then determined by comparing it with its 3D ground truth counterpart in terms of center-line distance and inter-vertex distances. Table3 reports, for each image, the median of the center-line polygon distances between reconstructed and ground truth polygons for that image. Also reported are the me- dians of the planimetric #28horizontal#29 and altimetric... In PAGE 7: ... For pairs of detected and ground truth polygons having the same number of vertices, the set of inter- vertex planimetric and altimetric errors were com- puted, and the medians of those measurements are shown in Table 4, broken down by the image in which the 2D polygons feeding the reconstruction process were hypothesized. Unlike the baseline er- ror data from Table3 , where the horizontal accu- racy of reconstructed polygon vertices was better than their vertical accuracy, here the situation is reversed, strongly suggesting that the planimetric component of reconstructed vertices is more sen- sitive to inaccuracies in the 2D polygon detection process than the altimetric component. This result is consistent with previous observations that the... ..."

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### Table 1: E ect of Bias on 3D Face Reconstruction

"... In PAGE 10: ...quation (9). We present here the results on the rst ve face models in the above mentioned database. Following the convention on the website, we refer to the ve subjects as quot;frame001 quot; to quot;frame005 quot;. From Table1 , we see that the peak value of the bias is a signi cant percentage of the true depth value. This happens only for a few points; however it has signi cant impact on the 3D face model because of interpolation techniques which, invariably, are a part of any method to build 3D models.... In PAGE 10: ... This happens only for a few points; however it has signi cant impact on the 3D face model because of interpolation techniques which, invariably, are a part of any method to build 3D models. The third and fourth columns in Table1 represent the root mean square (RMS) error of the reconstruction represented as a percentage of the true depth and calculated before and after bias compensation. The change in the average error after bias compensation is very small.... ..."

### Table 1. CCR in 3D_RMA (%)

2004

"... In PAGE 5: ...lassification of the probe sample. Fig. 7 shows the ROC curves for different data sets in MDB. From an overall view of Table1 , Fig.6-7, we can draw the following conclusions: a) The highest recognition is up to 96.... In PAGE 5: ... The feature vector containing the shape variation information improves the CCR distinctly (see Table 1). c) The increase of the training samples can improve the verification and identification performance (see Table1 and Fig.6-7).... In PAGE 5: ... d) Noise and volume of the tested database affect the CCR strongly. In Table1 , the CCR in ADB is lower than that in MDB. 5.... ..."

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