This week I came up with my initial approach for features for images (a bunch of blocks of percentage of key points of the images (i.e. 2×4 blocks). The exact number of blocks will be optimized once I have training/test data pictures. After collecting some photos with our camera at about 8m away, I have decided that only a certain section of the image will potentially contain the object we are trying to detect (in the middle of the image) based on the narrow lidar field of view, so my algorithm includes first cutting out that part of the image. My new algorithm will be to break that into a bunch of parts and see if any contain a runner/biker, and consider different sections for a car. Next week before the demo I need to implement that section breaking, and add some training and test data for the demo, though more will be added before the final project.