### Table 4. Performance comparisons on structured 3-dimensional polyhedron constraints

2003

Cited by 12

### Table 1: Description of all 3-dimensional CHPs.

1998

"... In PAGE 4: ...aybe strange formalism used by us was the basis for deriving structural results on e.g. 3D Hilbert indexings as presented in Section 4. So we can hardly imagine a comparatively simple presentation of all structurally di erent 3D Hilbert curves as given in Table1 there using other formalisms. 3.... In PAGE 10: ...C cannot even be the con- structor of a continuous curve of order 2. Table1 thus yields that there are exactly 4 28 + 2 28 = 6 28 structurally di erent CHPs. A complete classi cation of the high-dimensional cases appears to be much more di - cult.... ..."

Cited by 11

### Table 1: Description of all 3-dimensional CHPs.

1998

"... In PAGE 4: ...he basis for deriving structural results on e.g. 3D Hilbert indexings as presented in Section 4. So we can hardly imagine a comparatively simple presentation of all structurally di erent 3D Hilbert curves as given in Table1 (see Subsection 4.1) using other formalisms.... In PAGE 13: ...C cannot even be the constructor of a continuous curve of order 2. Table1 thus yields that there are exactly 4 28 + 2 28 = 6 28 structurally di erent CHPs. A complete classi cation of the high-dimensional cases appears to be much more di cult.... ..."

Cited by 11

### Table 1. Scene structure construction results.

1999

"... In PAGE 19: ... Each video clip is about 10-20 minutes long, and the total length is about 175,000 frames. The experimental results are shown in Table1 , where #5Cdetected scenes quot; denotes the number of scenes detected by the algorithm; #5Cfalse negatives quot; indicates the number of scenes missed by the algorithm; and #5Cfalse positives quot; indicates the number of scenes detected by the algorithm but are not considered as scenes byhuman. Since scene is a semantic level concept, the ground truth of scene boundary is not always concrete and this might be the reason that the authors of #5B17, 4#5D and #5B2#5D do not include the two columns of #5Cfalse negative quot; and #5Cfalse positive quot; in their experimental result tables.... In PAGE 20: ... The structure that most people agreed with is used as the ground truth of the experiments. From the results in Table1 , some observations can be made: #0F The proposed scene construction approachachieves reasonably good results in most of the movie types. #0F The approachachieves better performance in the #5Cslow quot; movies than in the #5Cfast quot; movies.... ..."

Cited by 59

### TABLE I. EFFECT OF TAMPERING ATTACKS ON SCENE STRUCTURE

### Table 1: Test Scenes

1990

"... In PAGE 3: ...ll experiments were conducted on a Sun 4 (SPARC) workstation running 4.0.3 UNIX1. Six di erent scenes were used as test cases, all of which are standard benchmarks (except for the DNA and the Arches models) and available in the public domain [13]. Ray statistics of these benchmarks are described in Table1 . All the images were computed at 512 by 512 resolution.... In PAGE 19: ... ops Reaching leaf node havg Determining face through which ray exits 15 Computing exit point 6 Extending ray into the next region 9 Total cost/region examined 30 + havg Table1 0: BSP/octree Traversal Operations Operation ops Plane intersection at each node 2 Branching decision at each node 1.5 Total cost to get to leaf node 3:5havg Table 11: K-d Traversal Operations within the rst few regions the ray encounters, then the BSP/octree method does less work.... In PAGE 19: ... ops Reaching leaf node havg Determining face through which ray exits 15 Computing exit point 6 Extending ray into the next region 9 Total cost/region examined 30 + havg Table 10: BSP/octree Traversal Operations Operation ops Plane intersection at each node 2 Branching decision at each node 1.5 Total cost to get to leaf node 3:5havg Table1 1: K-d Traversal Operations within the rst few regions the ray encounters, then the BSP/octree method does less work. This is because the k-d tree method determines the order (in advance) for regions that may never be visited by the ray because of early termination.... In PAGE 20: ...51 108.58 Table1 2: BSP Subdivision, no bounding volumes, BSP Traversal. 1.... In PAGE 29: ...0 71.3 Table1 3: Comparing the K-d Tree to other structures. beyond this point (this will cause the octree and BSP structures to subdivide) the k-d tree terminates itself when it realizes that no more bene ts can be obtained by further subdivision.... In PAGE 33: ...6 1.2 Table1 4: Voxel Statistics. The culling function is given by f(fmax(voxi;j;k) + rj 5 fmax(voxi;j;k)j) lt; fvg OR f(fmin(voxi;j;k) ? rj 5 fmax(voxi;j;k)j) gt; fvg where fmin(voxi;j;k) = min.... In PAGE 34: ...28 6.51 Table1 5: Timing Statistics. from three orthogonal directions, 24 slices in XY, 20 slices in YZ and 16 slices in XZ plane.... In PAGE 35: ...11 98.51 Table1 6: Results Using the Traditional Algorithm. three dimensional grid, we have an implementation that does not perform any culling or use any form of space partitioning.... ..."

Cited by 9

### Table 1. Scene structure construction results. movie name frames shots groups scenes

1998

Cited by 47

### Table 3. An example of general variable names expressing hierarchical structure of the scene

2001

"... In PAGE 3: ... WWW browser rtual world containing a room with a table and a chair. uppose an application chooses variable names according Table3 to express hierarchical organization of the cene. Consider a situation in which the variable Room.... In PAGE 3: ...Table quot; is locked. Table3 shows which variables be locked next. On the other hand, if the second user in the example bove was just changing the color of the table, he/she ould not interfere with the first user at all.... ..."

Cited by 3