In this paper, synergies between the recognition and tracking processes for
autonomous vehicle driving are studied. Object recognition is periodically
performed to focus attention on specific parts of the visual signal and to
assign them symbolic meanings. Tracking is used to maintain correspondence
s between objects identified at successive recognition instants as well as
to provide further features (e,g,, spatio-temporal trajectories) on which t
o base object-pose estimation. Results obtained by using complex road scene
s are reported, which demonstrate the validity of the approach in terms of
robustness, accuracy, and time responses.