Vehicle Detection and Tracking Project
This Project is based on the fifth task of the Udacity Self-Driving Car Nanodegree program. The main goal of the project is to create a software pipeline to identify vehicles in a video from a front-facing camera on a car.
Additionally, a lane line finding algorithm was added. See Lane Lines Detection Project for details.
It was implemented in Python with OpenCV and Scikit-learn libraries. Linear SVM was used as a classifier for HOG, binned color and color histogram features. The project repo is availuble on Github.
Contents:
Final project video:
The full project code is available on my Github
Project posts
01 Aug 2017
Image classification using SVM
Application of a linear SVM for image classification with HOG, binned color and color histogram features.
8 mins read