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Term 1. Project 5. Udacity Self-Driving Car Engineer Nanodegree. Vehicles detection classifier and vide processing pipeline

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Vehicles Detection with Computer Vision and Machine Learning Classifiers

Term 1

Project 5

Udacity Self-Driving Car Engineer Nanodegree.

Project description

The goals/steps of this project are the following:

  • Perform a Histogram of Oriented Gradients (HOG) feature extraction on a labeled training set of images and train a classifier Linear SVM classifier
  • Optionally, you can also apply a color transform and append binned color features, as well as histograms of color, to your HOG feature vector.
  • Note: for those first two steps don't forget to normalize your features and randomize a selection for training and testing.
  • Implement a sliding-window technique and use your trained classifier to search for vehicles in images.
  • Run your pipeline on a video stream (start with the test_video.mp4 and later implement on full project_video.mp4) and create a heat map of recurring detections frame by frame to reject outliers and follow detected vehicles.
  • Estimate a bounding box for vehicles detected.

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Term 1. Project 5. Udacity Self-Driving Car Engineer Nanodegree. Vehicles detection classifier and vide processing pipeline

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