PROJECT TITLE :

Feature-Based Roi Generation For Stereo-Based Pedestrian Detection - 2017

ABSTRACT:

Region of interest (ROI) generation is a vital step in stereo-based mostly pedestrian detection systems. During this paper, we propose an ROI generation method by fusing the colour and depth information obtained from a stereo camera mounted on a vehicle. In our proposed technique, a feature-primarily based method which uses contour properties of the image is used to find the ROIs. In our feature-based mostly ROI extraction technique, we tend to extract four features that are contour density, maximum area, maximum perimeter and matching score. Then we produce a feature vector from these features and classify them using SVM. ROIs are then classified into the pedestrian and non-pedestrian classes using Histogram of Oriented Gradients (HOG)/Linear SVM. We have a tendency to have tested our proposed method on the Daimler dataset and experimental results show that our proposed method has a 96.fivepercent accuracy for 1 false positive per frame and outperforms existing monocular and stereo-based strategies.


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