Real-time image recognition and processing has historically been a computationally intensive operation. However, with the advent of Haar-like features and cascading classifiers and their integration with the popular OpenCV library, this process has become much more accessible to the computer vision hobbyist. Using a relatively small pool of training data, users will be able to plan, build, and optimize a cascading classifier to recognize objects of their choosing in real time, with no more than the OpenCV library and a webcam. The goal of this poster is to provide a high-to-low level overview of these techniques, and allow beginners to learn to train and use their own image classifiers from scratch.