By Jonathan Harel, Christof Koch (auth.), Lucas Paletta, John K. Tsotsos (eds.)
This quantity constitutes the completely refereed post-workshop complaints of the fifth overseas Workshop on awareness in Cognitive structures, WAPCV 2008, held in Fira, Santorini, Greece in may perhaps 2008 as an linked occasion of the sixth foreign convention on desktop imaginative and prescient platforms (ICVS 2008).
The thirteen revised complete papers offered including with nine posters, were conscientiously chosen from 34 submissions. The papers are prepared in topical sections on consciousness in scene exploration, contextueal cueing and saliency, spatiotemporal saliency, attentional networks in addition to attentional modelling.
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This quantity constitutes the completely refereed post-workshop court cases of the fifth foreign Workshop on cognizance in Cognitive structures, WAPCV 2008, held in Fira, Santorini, Greece in may possibly 2008 as an linked occasion of the sixth foreign convention on desktop imaginative and prescient platforms (ICVS 2008). The thirteen revised complete papers offered including with nine posters, were rigorously chosen from 34 submissions.
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Additional info for Attention in Cognitive Systems: 5th International Workshop on Attention in Cognitive Systems, WAPCV 2008 Fira, Santorini, Greece, May 12, 2008 Revised Selected Papers
For the anatomical constraint of possible ﬁnger positions the energy function is based on the Hopﬁeld associative memory approach : E(yi ) = − Tij · yi · yj . (4) ij i=j The minimum of the function is determined by the matrix Tij . For Tij s greater than zero, the corresponding yi s should either stay zero or become active in order to minimize the energy function. In the associative memory approach, Tij is determined by a learning rule. Here, we chose the Tij so that the hand network fulﬁls the anatomical constraints.
2. Excitatory connections between ﬁngers indicate appropriate locations for the ﬁngers and the thumb (see Fig. 1 for an illustration). The results of the separation feed into the corresponding ﬁnger maps providing the hand network with the geometrical constraints. Note that, of course, the assumptions about the object- and background-colours represent a strong simpliﬁcation. On the other hand, this mechanism can be interpreted as mimicking the result of stereo vision. In such a resulting “depth image” real edges suitable for thumb or ﬁngers could be easily identiﬁed.
Decoding What People See from Where They Look 21 in Fig. 6% of trials, compared to 25% for chance, with null hypothesis that predictions are 25% correct being rejected at p < 10−4 . We also tested the prediction rates when ﬁxations were pooled over progressively fewer subjects, instead of only nine as above. For this, we used only the CIO+F map (although the face channel shows the highest decoding performance we wanted to use a feature map that combines bottom-up features to match common attention prediction methods), and binary image trials (one decoy).