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  • 1
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract In short, the model consists of a two-dimensional set of edge detecting units, modelled according to the zero-crossing detectors introduced first by Marr and Ullman (1981). These detectors are located peripherally in our synthetic vision system and are the input elements for an intelligent recurrent network. The purpose of that network is to recognize and categorize the previously detected contrast changes in a multi-resolution representation of the original image in such a manner that the original information will be decomposed into a relatively small numberN of well-defined edge primitives. The advantage of such a construction is that time-consuming pattern recognition has no longer to be done on the originally complex motion-blurred images of moving objects, but on a limited number of categorized forms. Based on a numberM of elementary feature attributes for each individual edge primitive, the model is then able to decompose each edge pattern into certain features. In this way anM-dimensional vector can be constructed for each edge. For each sequence of two successive frames a tensor can be calculated containing the distances (measured inM-dimensional feature space) between all features in both images. This procedure yields a set ofK—1 tensors for a sequence ofK images. After cross-correlation of allN ×M feature attributes from image (i) with those from image (i+1), wherei = 1, ...,K - 1, probability distributions can be computed. The final step is to search for maxima in these probability functions and then to construct from these extremes an optimal motion field. A number of simulation examples will be presented.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Journal of comparative physiology 165 (1989), S. 179-192 
    ISSN: 1432-1351
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Medicine
    Notes: Summary Experiments, involving sequential micro-stimulation of two (or more) adjacent neuroommatidia in the compound eye of the blowfly,Calliphora erythrocephala (Mg.), are presented. These experiments, using brief flashes of 3 ms duration with low intensities in the order of 8·10−3 Cd/m2, are performed to isolate individual response contributions of single Elementary Movement Detectors in the input micro-circuitry of the motion-sensitive directionally-selective H1-neuron (Figs. 4 through 6). A two-dimensional mapping of single EMD contributions to the overall response will be presented for the dark adapted eye (Fig. 7). It is concluded that under such low illumination levels (when compared to normal daylight situations, where illumination typically varies between 1 and 200 Cd/m2), contributions from EMD's with sampling bases up to 8Δ φ h, oriented along the horizontal sensitivity axis of the neuron, contribute to the total response of the neuron. In addition, results will be presented for similar experiments, in which various backgrounds with different sizes and intensities are superimposed on the sequence of stimulus flashes (Fig. 8). The dependence of the relative contributions for the smallest four sampling bases (i.e. 2, ..., 8 timesΔ φ h) on background size, background intensity and distance of the background field to the projections of the flashes, will be discussed. Supplementary experiments (Figs. 9 through 12) will be presented, which indicate that when in addition to an ongoing sequence in (for instance) the null direction, thus inhibiting the activity of the neuron, a second sequence is presented somewhere in the receptive field of the H1-neuron, the total response is a non-linear combination of both individual responses. Interpretation in terms of a pooling correlation scheme, which, over a limited target region, sums the activities of the EMD's in a highly non-linear fashion, provides a qualitative explanation.
    Type of Medium: Electronic Resource
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