The computer vision-based vehicle detection has several applications. Among those fast detection of moving vehicles is crucial for safe autonomous urban driving. With the ultimate goal of building autonomous vehicles; many government institutions have lunched various projects worldwide. These efforts have produced several prototypes and solutions, based on different approaches. The laser range finders provides reliable detection of moving vehicles from a high-speed moving platform. To overcome the low signal-to-noise ratio we presenting a notion of motion evidence that arises during rapid detection of moving vehicles in noisy urban environments. We also describe an array of optimization techniques that enable accurate detection in real time. This paper provides a critical survey of recent vision-based on-road vehicle detection systems from the most challenging situations presented at the Urban Grand Challenge as well as other urban settings. Keywords: motionevidence,DynamicBayesiannetworkmodel,IBEOAlasca,HDL-64E,signal-to-noise
On Road Vehicle Detection System Using Ibeo Alasca And Velodyne Hdl-64e Sensors
2017-01-13
doi:10.26483/ijarcs.v5i2.2003
International Journal of Advanced Research in Computer Science; Vol 5, No 2 (2014): SPECIAL ISSUE I March 2014 ; 0976-5697 ; 10.26483/ijarcs.v5i2
Article (Journal)
Electronic Resource
English
DDC: | 629 |
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