The STUDIA UNIVERSITATIS BABE┼×-BOLYAI issue article summary

The summary of the selected article appears at the bottom of the page. In order to get back to the contents of the issue this article belongs to you have to access the link from the title. In order to see all the articles of the archive which have as author/co-author one of the authors mentioned below, you have to access the link from the author's name.

 
       
         
    STUDIA INFORMATICA - Issue no. 2 / 2015  
         
  Article:   OBSTACLE RECOGNITION IN TRAFFIC BY ADAPTING THE HOG DESCRIPTOR AND LEARNING IN LAYERS.

Authors:  .
 
       
         
  Abstract:   Despite many years of research, obstacle recognition is still a dicffiult, but very important task. We present a multi-class approach, that extracts from images the Histogram of Oriented Gradients (HOG) based on aspect ratio of Region of Interest (ROI) and use them in a multi-class classi fication problem. For the learning phase we propose an original approach based on decision trees. Numerical experiments are performed on a benchmark dataset consisting of animal, pedestrian, car and sign (labeled) images captured in outdoor urban environments and indicate that the proposed model is able to improve the performance of the recognition process.

2010 Mathematics Subject Classi fication. 68T05, 91E45.
Key words and phrases. Multiclass classi cation, HOG, Decision Trees, Boosting.
 
         
     
         
         
      Back to previous page