Vehicle Detection and Tracking
23 Feb 2017
In this project, the goal is to write a software pipeline to detect vehicles in a video.
Results
The following videos show the final results of the vehicles being detected on two different tracks with varying difficulty:
| Project Track | Challenge Track |
|---|---|
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The 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
- Apply a color transform and append binned color features, as well as histograms of color, to your HOG feature vector.
- Normalize features and randomize a selection for training and testing.
- Implement a sliding-window technique and use trained classifier to search for vehicles in images.
- Run pipeline on a video stream 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.