### Table 1: Comparison of some 3D reconstruction methods. Lexicographic ordering was used so that (i) the importance of criterion decreases from the first to the last column and (ii) the quality of the method raises from upper to lower row.

### Table 1. Comparison of some 3D reconstruction methods. Lexicographical ordering was used so that (i) the importance of a criterion decreases from the first to the last column and (ii) the quality of the method decreases from top to down

2002

"... In PAGE 5: ... Subsequent images are taken one after another and used to extend and improve actual reconstruction. Table1 summarizes the differences among the mentioned methods. Jacobs [8] solves reconstruction with occlusions for orthographic camera, Sturm amp; Triggs [11] solve reconstruction without occlusions for perspective cam- era.... ..."

Cited by 20

### Table 1: Comparison of some 3D reconstruction methods from points. Lexico- graphical ordering was used so that (i) the importance of a criterion decreases from the first to the last column and (ii) the quality of the method decreases from top to down

### Table 2. Criterions for Quality Assurance

### Table 2: Mesh quality improvement for rand2 with swapping. that some local mesh quality measure be improved before accepting a change in vertex location. Any local quality criterion suitable for use with the optimization-based smoothing can be used in this context. For optimization-based smoothing, we present results for ve di erent objective functions: 1. Maximize the minimum dihedral angle (maxmin angle) 2. Minimize the maximum dihedral angle (minmax angle) 3. Maximize the minimum cosine of the dihedral angles (maxmin cosine) 4. Minimize the maximum cosine of the dihedral angles (minmax cosine) 5. Maximize the minimum sine of the dihedral angles (maxmin sine) We expect nearly identical results, though not necessarily identical convergence behavior, from two pairs of these measures:

1996

Cited by 30

### Table 5: Classi cation of Quality Criteria for MBISs

1999

"... In PAGE 8: ... Also, we have added the two criteria which play a particularly important role for MBIS, namely reliability and price, and have split the accessibility criterion. Table5 summarizes and categorizes the criteria used. As usual, we assume independence of the criteria.... In PAGE 8: ...Table 5: Classi cation of Quality Criteria for MBISs Please note that for such a classi cation it is not always clear which criterion ts in which class of Table5 . For instance, if sources charge the same amount of money for each query, the price criterion should be only source-speci c.... In PAGE 15: ...e., one dimension for each non-source-speci c criterion of Table5 . The criterion category speci es how the scores for the individual criteria are determined: QCA-speci c criteria have xed scores for each QCA.... ..."

Cited by 71

### Table 2: The values of the entropy and the purity with di erent convergence criterion.

2003

"... In PAGE 12: ...3 Convergence criterion and number of iterations We now discuss the convergence criterion used in the K-means and in the hybrid algo- rithm and how it in uences the performance of these algorithms. We can see from the Table2 that when we increased the value of a little bit (from 0.1 to 0.... In PAGE 13: ...Table 2: The values of the entropy and the purity with di erent convergence criterion. the Table2 , the quality of the clusters obtained with = 0:3 is very close to that obtained with = 0:1. It suggests that when we run the hybrid algorithm, we may use a larger value to reduce the parallel run time while keeping a satisfactory clustering quality.... ..."

### Table 2: Rating scores of alternatives in terms of each criterion

2002

"... In PAGE 3: ... A scale from 1 (least desirable) to 9 (most desirable) was used in this example. Table2 shows the rating scores of alternatives in terms of each criterion. Table 1: Weights of six quality criteria Criterion Weight availability 0.... In PAGE 4: ...Applying Formula 3.1 to Table2 , we obtain the final ranking scores as a0a2a1a4a3a6a5 = 7.14, a0a7a1a4a3a6a8 = 8.... ..."

### Table 5: Mesh quality improvement for rand1 with both swapping and smoothing An important question in any local smoothing algorithm is the number of smoothing passes required to improve the mesh to the point where further improvement is negligible. Table 6 shows the e ect of various numbers of smoothing passes with the maxmin sine criterion on rand1. Similar results for rand2 with the maxmin angle criterion can be found in Appendix A. In both cases swapping was used before smoothing. In each case, mesh quality improves only negligibly after the fourth or fth smoothing pass. We conclude this subsection with a comparison of the computational e ciency of the various mesh improvement techniques. Table 7 compares timings for mesh improvement using swapping, smoothing, and a combination of the two for rand2 on a 110 MHz SPARC 5. The times for the swapping-only cases indicate that edge swapping, while very bene cial,

1997

"... In PAGE 15: ...20 0.017 0 0 Table 4: Comparison of the e ectiveness of smoothing for four di erent swapping options (mesh rand1, edge swapping enabled, maxmin sine smoothing) Table5 shows the results for rand1 using the local reconnection procedure given in Recommendation 3 followed by each of the eight smoothing options discussed in the preceding section. The distribution of dihedral angles for each random mesh improves signi cantly regardless of the choice of smoothing criterion.... ..."

Cited by 55