ABSTRACT
Autonomous vehicles are already a reality, and there are still several
challenges to overcome. One important challenge for the adoption
of these vehicles is perceiving its surroundings. This necessity of
perception can be fulfilled by digital cameras. When working with
digital image processing, the quality will be limited by real-time
constraints. As several works indicate, this real-time constraint for
autonomous vehicles is at most 100ms per frame. Also, by improving
the processing time, the chances of accidents involving autonomous
vehicles may be decreased. This paper analyses the advantages and
drawbacks of semantic segmentation and also presents a study to
implement perception for autonomous vehicles by accelerating a
semantic segmentation algorithm, also used by other works on the
field. To accelerate the algorithm, spacial parallelism will be used.