Computer vision plays a key role in vehicle technology, some examples are advanced driver assistance systems (ADAS), exploratory and service robotics, unmanned aerial vehicles and underwater robots. In addition to traditional applications such as lane departure warning, traffic object recognition, visual odometry or trajectory planning, new challenges are arising: learning and evaluation with reduced groundtruth/testing data, on–board calibration for multi–cameras, SLAM in natural scenarios, etc.<br>The goal of the 4th CVVT:E2M workshop is to get together researchers in computer vision for vehicular technologies, in order to and promote development and spreading of new ideas and results across the aforementioned fields. We invite the submission of original research contributions in computer vision addressed to:<br>– Autonomous navigation and exploration based on vision and 3D measurements<br>– Vision–based advanced driver assistance systems<br>– Vision–based underwater and unmanned aerial vehicles<br>– Visual driver monitoring and driver–vehicle interfaces<br>– On–board calibration of multi–camera acquisition systems (stereo rigs, multimodal, networks)<br>– Non–verbal and graphical information for long–distance exploration<br>– Performance evaluation in navigation, exploration and driver–assistance<br>– Machine learning techniques in visual navigation, exploration and driver–assistance<br>
Abbrevation
CVVT:E2M
City
Sydney
Country
Australia
Deadline Paper
Start Date
End Date
Abstract