The detection of objects on a given road path by vehicles equipped with range measurement
devices is important to many civilian and military applications such as obstacle avoidance in
autonomous navigation systems. In this thesis, we develop a method to detect objects of a
specific size lying on a road using an acquisition vehicle equipped with forward looking Light
Detection And Range (LiDAR) sensors and inertial navigation system. We use GPS data to
accurately place the LiDAR points in a world map, extract point cloud clusters protruding from
the road, and detect objects of interest using weighted random forest trees. We show that our
proposed method is effective in identifying objects for several road datasets collected with
various object locations and vehicle speeds.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.