@inproceedings{SisLab2614,
       booktitle = {2018 The International Conference on Recent Advances in Signal Processing, Telecommunications \& Computing (SigTelCom)},
           month = {January},
           title = {Real-time Lane Marker Detection Using Template Matching with RGB-D Camera},
          author = {Cong Hoang Quach and Manh Duong Phung and Minh Trien Pham and Hung Nguyen and Thang Nguyen and Van Lien Tran},
            year = {2018},
             url = {https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2614/},
        abstract = {This paper addresses the problem of lane
detection which is fundamental for self-driving vehicles.
Our approach exploits both colour and depth information
recorded by a single RGB-D camera to better deal with
negative factors such as lighting conditions and lane-like
objects. In the approach, the colour and depth images
are first converted to a half-binary format and a 2D
matrix of 3D points. Those representations are then used
as inputs of template matching and geometric feature
extraction processes to calculate a response map that
its values present the probability of pixels being lane
markers. To enhance the result, the principal component
analysis and lane model fitting techniques are employed
to refine the template and form lane surfaces. A number
of experiments have been conducted on both synthetic
and real datasets. The result shows that the proposed
approach can effectively eliminate the unwanted noise
to accurately detect lane markers in various scenarios.
With the hardware configuration of a popular laptop
computer, the program implementation operates at the
speed of 20 frames per second which is sufficient for
real-time autonomous driving applications.}
}