Page 128 - Dynamic Vision for Perception and Control of Motion

112 4 Application Domains, Missions, and Situations

lected for presentation in this book. An all-encompassing and complete ontology
for ground vehicles would be desirable but has not yet been assembled in the past.
From the general environmental conditions grouped under A.1, up to now only
a few have been perceived explicitly by sensing, relying on the human operator to
take care for the rest. More autonomous systems have to have perceptual capabili-
ties and knowledge bases available to be able to recognize more of them by them-
selves. Contrary to humans, intelligent vehicles will have much more extended ac-
cess to satellite navigation (such as GPS now or Galileo in the future). In
combination with digital maps and geodetic information systems, this will allow
them improved mission planning and global orientation.
Obstacle detection both on roads and in cross-country driving has to be per-
formed by local perception since temporal changes are too fast, in general, to be re-
liably represented in databases; this will presumably also be the fact in the future.
In cross-country driving, beside the vertical surface profiles in the planned tracks
for the wheels, the support qualities of the ground for wheels and tracks also have
to be estimated from visual appearance. This is a very difficult task, and decisions
should always be on the safe side (avoid entering uncertain regions).
Representing national traffic rules and regulations (Appendix A.1.1) is a
straightforward task; their ranges of validity (national boundaries) have to be
stored in the corresponding databases. One of the most important facts is the gen-
eral rule of right- or left-hand traffic. Only a few traffic signs like stop and one-way
are globally valid. With speed signs (usually a number on a white field in a red cir-
cle) the corresponding dimension has to be inferred from the country one is in
(km/h in continental Europe or mph in the United Kingdom or the United States,
etc.).
Lighting conditions (Appendix A.1.2) affect visual perception directly. The dy-
namic range of light intensity in bright sunshine with snow and harsh shadows on
dark ground can be extremely large (more than six orders of magnitude may be en-
countered). Special high-dynamic-range cameras (HDRC) have been developed to
cope with the situation. The development is still going on, and one has to find the
right compromise in the price-performance trade-off. To perceive the actual situa-
tion correctly, representing the recent time history of lighting conditions and of po-
tential disturbances from the environment may help. Weather conditions (e.g., blue
skies) and time of day in connection with the set of buildings in the vicinity of the
trajectory planned (tunnel, underpass, tall houses, etc.) may allow us to estimate
expected changes which can be counteracted by adjusting camera parameters or
viewing directions. The most pleasant weather condition for vision is an overcast
sky without precipitation.
In normal visibility, contrasts in the scene are usually good. Under foggy condi-
tions, contrasts tend to disappear with increasing distance. The same is true at dusk
or dawn when the light intensity level is low. Features linked to intensity gradients
tend to become unreliable under these conditions. To better understand results in
state estimation of other objects from image sequences (Chapters 5 and 6), it is
therefore advantageous to monitor average image intensities as well as maximal
and minimal intensity gradients. This may be done over entire images, but comput-
ing these characteristic values for certain image regions in parallel (such as sky or
larger shaded regions) gives more precise results.