![](bg8.png)
is relatively reliable, so predicted path may be con-
strained by applying a semantic segmentation map
of the scenes and removing those paths that are not
adjacent to regions classified as road and sidewalk.
Specifically for the case of cameras mounted on a ve-
hicle, the next work is to include the ego-motion. Fi-
nally, to tackle the problem of representing the posi-
tion of objects on an image coordinate by pixels and
its sensitivity, it would be interesting to see the im-
age as a grid, and represent the position of the object
according to this grid.
ACKNOWLEDGEMENTS
This work has received funding from EU H2020
Project VI-DAS under grant number 690772 and
Insight Centre for Data Analytics funded by SFI,
grant number SFI/12/RC/2289. The GPU GeForce
GTX 980 used for this research was donated by the
NVIDIA Corporation.
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