108
0.6 T T T T T T 8
R TASTE =
os] edge detection -— 7
6r
0.4
Sr i
03} | |
4}
= 02 Fonero Pm
|. | min | max | mean | 3}
R, T, STR 0.320 | 0.550 | 0.390 eur 7 2}
À 0.027 | 0.220 | 0.063 . : : : : ; : : : : : :
[R, T, STR, A [| 0.230 | 0.480 | 0.280 | 8S s 0.2 " " 7 $2 0o e om m
Table 2: Computing time of edge detection, pure recognition and inter-
action between R, T, A, STR (left); x-axis: frames, y-axis: time in [sec].
Table 1: Computing time per image Changing between levels of abstraction in case of interaction (right) ;
measured on a HP9000/735 in [sec]. x-axis: frames, y-axis: levels of abstraction.
detected by the attention control. The recognition is initiated to verify the attention field (middle, first row).
After 5 frames the recognized object changes to ’tracking’ (left, second row), the attention control looks for new
objects in the scene (middle, second row) and the recognition waits for new input (right, second row).
s 3 wr
£ N 5
t
1 x
? »
T Ai. ex 2 ie) —
re me x 7 :
SX a m— = i Ea
S eterne i= A US oum:
~~ 7
i
e SS
du pid
> Ni
= A
à if ; jd
fe. ee
4 em a p /
ep
a x X > =
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Figure 4: Interaction between tracking (left), attention control (middle) and recognition (right)
Examples of results obtained only by attention control are shown in Fig. 5.
6. OUTLOOK
Today we get nearly the same robust results with integrated attention control than before. With regard to this
we will try to improve MOSAIK's attention control. For an exact evaluation we will test the attention control
on more scenes in the future. :
Now MOSAIK needs factor 7 to the video tact rate of 25Hz on a standard monoprocessor platform.
We are optimistic to satisfy real time requirements with the next standard cpu generation.
Acknowledgement
The work reported here was done in cooperation with the FORWISS research group Cognitive Systems, Munich;
the support of BMW AG, who supplied the image sequences, is gratefully acknowledged.
IAPRS, Vol. 30, Part 5W1, ISPRS Intercommission Workshop “From Pixels to Sequences”, Zurich, March 22-24 1995