![](bg6.png)
Figure 8: Shows some more results from Google Earth images.
Figure 7: Illustrates the performance of the two-stage algo-
rithm on Google Earth data set.
Table 2: Performance of our two-stage approach
No. of images
processed
No. of cars Overall
RR
Overall PR
36 374 90% 94%
The overall recall and precision rate gives a clearer picture
of an impressive performance obtained through our
approach.
two strong classifiers one after the other. In the pro-
cess, we improve the detection rate of the first clas-
sifier in order not to miss objects in the first stage
and improve the precision of the second classifier.
Hence, we were able to achieve a high recall rate and
with very high precision rate. We have achieved very
good results in terms of accuracy, however, to make
it a robust system, more work in this direction is re-
quired. Knowing that the proposed system performs
well, we would be interested in a faster implementa-
tion of sophisticated approach such as part-based de-
tection methods so that we are able to detect objects in
large images in real time. Besides, we expect to de-
velop a more efficient rotation-invariance scheme to
be used in the first stage.
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