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Chapter 4. Simulating Visual Attention for Crowds
4.3.2 Speed
For speed, we follow the same principle as for the proximity parameter. It is calculated as:
Ss(t) =ωsw||de(t) − dc(t)|| (4.5)
where ||de(t) − dc(t)|| is the relative speed, corresponding to the difference in distance traveled
by C and E in one frame, and ωsw is a weighting factor to bring the elementary speed
scores to vary in the same range as the proximity scores.
4.3.3 Orientation
Similarly, our orientation score is computed as:
So(t) =(π − α(t))β(t) (4.6)
The larger the angle α, the more opposite the direction of E is in comparison to the direction
of C. We want to give more importance to the entities coming towards C. We therefore
weight the orientation score in order for the entities in the central vision to be favored as
opposed to the entities in the peripheral vision.
4.3.4 Periphery
The last criterion is the periphery. This actually works just as the orientation. Calculations
are the same, however, we give more importance to the entities in the periphery. The smaller
the angle, the closer the direction of E is in comparison to the direction of C. Entities
entering the field of vision will thus have small angle values. The periphery score is therefore
calculated as:
Spe(t) =
0 if β(t) >βm
ωpwα(t)(π − β(t)) otherwise
(4.7)
where βm is the maximum angle between the forward directions of C and E. Here as well,
we weight the score with a weighting parameter ωpw for the score range to be similar to that
of the other criteria. We thus obtain all our subscores.
It is important to note that we further improve our algorithm by pruning a number of
computations. Indeed, brute force computation proved to be counterproductive. For example,
all entities farther than a certain distance from C need not be computed. We therefore
prune the scores computation for each entity E. First, we use the maximum distance dm.
All entities farther than this from C are automatically discarded from further computation.
Out of this subset of entities, we prune the process once more by considering only those in
C’s field of view. All following computations are done solely on this remaining subset of
entities. We thus greatly reduce computational costs.
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