Abstract
Cameras allow for highly accurate identification of targets. However, it is difficult to obtain spatial position and velocity information about a target by relying solely on images. The millimeter-wave radar (MMW radar) sensor itself easily acquires spatial position and velocity information of the target but cannot identify the shape of the target. MMW radar and camera, as two sensors with complementary strengths, have been heavily researched in intelligent transportation. This article examines and reviews domestic and international research techniques for the definition, process, and data correlation of MMW radar and camera fusion. This article describes the structure and hierarchy of MMW radar and camera fusion, it also presents its fusion process, including spatio-temporal alignment, sensor calibration, and data information correlation methods. The data fusion algorithms from MMW radar and camera are described separately from traditional fusion algorithms and deep learning based algorithms, and their advantages and disadvantages are briefly evaluated.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
