Reliable detection and classification of vulnerable road users constitute a critical issue on safety/protection systems for intelligent vehicles driving in urban zones. In this subject, most of the perception systems have LIDAR and/or Radar as primary detection modules and vision-based systems for object classification. This work, on the other hand, presents a valuable analysis of pedestrian detection in urban scenario using exclusively LIDAR-based features. The aim is to explore how much information can be extracted from LIDAR sensors for pedestrian detection. Moreover, this study will be useful to compose multi-sensor based pedestrian detection systems using not only LIDAR but also vision sensors. Experimental results using our data set and a detailed classification performance analysis are presented, with comparisons among various classification techniques.


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    Title :

    Exploiting LIDAR-based features on pedestrian detection in urban scenarios


    Contributors:


    Publication date :

    2009-10-01


    Size :

    945219 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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