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5.5. Detection examples 76
parameter ”Box” ”Group” ”Doors”
cornerness threshold of Harris detector p h 1 1 1
sigma of Harris detector p s 0.5 0.5 0.5
stability parameter p r 5 5 5
Table 5.1: Parameter values used for the detection examples.
value for p s would be in the range of 0.5 − 1.5.
Stability parameter p r : The last parameter is the stability parameter p r . The parameter
decides on the stability of a cluster and if the cluster should be selected as region. If a
cluster fulfills the stability criteria for p r threshold steps the cluster is denoted as stable.
The thresholds start with the minimal edge length in pixel and are increased by 1 pixel
each step until the maximal edge length is reached. A high value produces only very stable
clusters and lower values less stable clusters. Useful values for p r are in the range of 5−10.
5.5 Detection examples
This section shows detection examples for three different image sequences. Each sequence contains
images with increasing view point change up to wide-baseline cases. This is to demonstrate
the repeatability of the MSCC detector under viewpoint change. The interest points are shown
as red crosses while the MSCC regions are shown as blue ellipses.
”Box” scene: Figure 5.8 shows the MSCC detections for the ”Box” scene. The ”Box” scene
is a set of images of a box from different viewpoints. The images were acquired on a
turntable. The images are of a resolution of 800 × 600 pixel. Many regions are detected
repetitively in each image. The multi-scale clustering detects very small as well as large
regions.
”Group” scene: Figure 5.9 shows the MSCC detections for the ”Group” scene. The scene
consists of two piecewise planar objects on a turntable. The overall viewpoint change for
the whole image sequence is almost 90 ◦ . Again many regions are detected repetitively in
each image despite of the large viewpoint change. The image resolution is 1024×896 pixel.
”Doors” scene Figure 5.10 shows the MSCC detections for the ”Doors” scene. The ”Doors”
image set is from a robot localization experiment. The image resolution is 720 × 288. The
poster in the example contains a lot of written text. The MSCC detector manages to
identify the different sections of the text as MSCC regions.
The parameter settings for the 3 scenes are given in Table 5.1.