@inproceedings{scholars3281,
           title = {On-road approaching motorcycle detection and tracking techniques: A survey},
         address = {Penang},
         journal = {Proceedings - 2013 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2013},
           pages = {63--68},
            note = {cited By 8; Conference of 2013 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2013 ; Conference Date: 29 November 2013 Through 1 December 2013; Conference Code:102703},
             doi = {10.1109/ICCSCE.2013.6719933},
            year = {2013},
          author = {Mukhtar, A. and Xia, L. and Boon, T. T. and Abu Kassim, K. A.},
            isbn = {9781479915088},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894197419&doi=10.1109\%2fICCSCE.2013.6719933&partnerID=40&md5=ac5abbe22ea2bbce8153a55933259481},
        abstract = {Driver Assistance System (DAS) plays a vital and promising role in most intelligent vehicles technologies by alerting the motorists about any possible collision. In such systems robustness, reliability and real-time detection are critical. This paper focused on on-road detection of approaching motorcycles, where sensor is preferably attached on the rear side of vehicle. More attention is given to the applicability of methods and technologies on motorcycle detection and recognition, as motorcycles are smaller and harder to be noticed by vehicle driver. First we discuss the problem of on-road motorcycle detection using different sensors followed by review of motorcycle detection research. Then, we discuss types of sensor to set the stage for vision-based motorcycle detection. Methods used for hypothesis generation (HG) and hypothesis verification (HV) are mentioned before the integration of detection and tracking systems. Finally, we present a critical overview of the methods discussed and assess the potential of these methodologies for the future research and applications. {\^A}{\copyright} 2013 IEEE.}
}