next up previous
Next: Relation to Other Work Up: Surface Clusters Previous: Theory of Surface Clusters

Examples of Surface Cluster Formation

To show that the implemented computation produced suitable results, an example is given here, using the surface hypotheses of the test image (see Figure 4.8). Some of the surface clusters for this scene are shown in Figures 5.5, 5.6 and 5.7.

Figure 5.5: Several Primitive Clusters
\begin{figure}\epsfysize =5in
Figure 5.6: An Equivalent Depth Cluster
\begin{figure}\epsfysize =4in
Figure 5.7: Several Depth Merged Clusters
\begin{figure}\epsfysize =5in

As can be seen in these examples, the surface clusters form object level "chunks" of the image, and correspond to the primitive ASSEMBLYs of the models given in Chapter 7. In Table 5.1, there is a listing of the surface cluster to model ASSEMBLY correspondences for the test image. Clearly, the surface cluster formation process isolates the key features into what corresponds to structurally based intuitive "objects".

Table 5.1: Surface Cluster To Model Correspondences
1 PRIMITIVE 20,21,30
3 PRIMITIVE 16,26 robshldbd
4 PRIMITIVE 8 robbody
5 PRIMITIVE 29 robshldsobj
6 PRIMITIVE 33,34,35,36,37
7 PRIMITIVE 12,18,31 lowerarm
8 PRIMITIVE 9,28,38 trashcan
9 PRIMITIVE 17,19,22,25,32 upperarm
10 EQUIVALENT 20,21,27,30
11 EQUIVALENT 8,16,26,29 robshould + robbody
12 EQUIVALENT 9,12,18,28,31,38 lowerarm + trashcan
13 DEPTH 9,12,17,18,19,22,25,28,31,32,38 armasm + trashcan
14 DEPTH 8,16,17,19,22,25,26,29,32
15 DEPTH 8,9,12,16,17,18,19,22,25,26,28,29,31,32,38 link + robot + trashcan
16 DEPTH 8,16,20,21,26,27,29,30
17 DEPTH 8,16,17,19,20,21,22,25,26,27,29,30,32
18 DEPTH 8,9,12,16,17,18,19,20,21,22,25,26,27,28,29,30,31,32,38

Figure 5.8: Surface Cluster Hierarchy
\begin{figure}{\setlength{\unitlength}{1mm}{\hfill\hbox to 5.15in{\hrulefill}\hf...
...end{picture}\end{center}{\hfill\hbox to 5.15in{\hrulefill}\hfill}
Figure 5.8 shows the surface clusters of Table 5.1 organized to make explicit their hierarchical relationships. Clusters designated by squares closely correspond to models.

For the example above, the primitive and equivalent depth surface clusters are appropriate. What seems to be a problem is the number of depth merged surface clusters, which depend on combinatorial groupings of equivalent depth surface clusters. For the test scene, there are 9 primitive, 3 equivalent depth and 6 depth merged surface clusters. Here, the number of depth merged surface clusters is not such a problem as the object also has a strong depth order, so 2 of the 6 correspond to ASSEMBLYs. In other test images, shallower depth ordering causes more serious combinatorial grouping. Hence, an alternative process should be considered.

Though several surface clusters contained multiple ASSEMBLYs, this caused no recognition failures.

next up previous
Next: Relation to Other Work Up: Surface Clusters Previous: Theory of Surface Clusters
Bob Fisher 2004-02-26