Bernal S D_2010.pdf - University of Plymouth

5,1. FEEDFORWARD PROCESSING
using the CI features of the maxinimn S2 prototypes al each location. This graphical view of
the S2 internal representation is limited in that it is based only on one of the 250 values of each
distribution.
Figure 5.6 shows the likelihood response of the C2 nodes, A(C2), at all locations and RF sizes.
The figure also includes a reconstruction of the C2 interna] representation using the C' I features
corresponding to the maximum C2 prototype at each location. This graphical view of the C2
internal representation is iiinited in that it is based only on one of the 2500 values of each
distribution. Also, due to the large size and great overlap between the Rf of the C2 nodes,
the maximum feature is likely lo be the same for adjacent nodes. Note the C2 response is
shown for the alternative 3-level architecture (based on Yamane eta!. (2006)), such that different
architectures will exhibit different number of nodes, for instance the 3-level architecture has
only one C2 node.
Figure 5.7 shows the likelihood response of the S3 nodes, A(53), at all lixralions and RF sizes
of the alternative 3-layer architecture. In this case the input image used was the 24th object of
the dataset, which corresponds to S3 states 93 to 96 of the 240. To recap, in this architecture
there are four S3 prototypes for each object, corresponding to four different possible locations
of the object al theC2 level. Beside the maximum value of each distribution is shown an image
which symbolically corresponds lo the S3 prototype of that S3 stale. Note that, in most cases,
the winner element corresponds to a prototype of the input image, although in some cases there
might exist some ambiguity and other similar object prototypes may exhibit relatively large
values.
For further details see the ligure captions.
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