This document reviews object tracking based on the K-nearest neighbors (KNN) classifier. It discusses how the KNN classifier can be used to differentiate targets from backgrounds in images to provide accurate real-time object tracking. The KNN classifier is a simple machine learning algorithm that classifies new data based on similarity to training data. It discusses applications of KNN in object tracking, pattern recognition, and other domains. While KNN provides effective classification with intuitive explanations, it has limitations such as sensitivity to parameter selection and high computational costs for large datasets.