Vehicle detection for self driving cars
Building a data pipeline to detect vehicles on the road I am working on building a data pipeline to detect vehicles from a video feed for a self driving car. Various computer vision techniques are used, including Histogram of Oriented Gradients (HOG), as well has a sliding window approach combined with a machine learned classifier. The general steps for creating this data pipeline are as follows: 1. Perform a histogram of oriented gradients (HOG) feature extraction process on a labeled training set of images. 2. Use the output of the HOG to train a supervised classifier (SVM, neural network, etc.) 3. Implement a sliding window technique with windows of various sizes using the trained classifier to search for vehicles in the images using the classifier. 4. Create a heat map of recurring detections. Create a overlap threshold to reject false positives. Also estimate a bounding box based on pixels detected. The data...