This week I continued to work on and implement the image processing part of the project. I implemented the part to pick the section of the image the object we are trying to detect probably is in, based on which section has the most edges after blurring. I also implemented a k-nearest neighbors classifier. I have also put together the full workflow for the object recognition part (so the only parts that need to be improved are all of the individual functions, etc.). Next week I would like to get some pictures with our camera at the right distance of runner’s, biker’s, and car’s so I can improve the section picking algorithm and start testing with them. I would also like to start implementing the feature extraction from the key points part, and hopefully have enough with that for decent classification by the demo.