Motion Vector

Motion vectors represent the displacement of image features or data points over time, serving as crucial information in various applications like video processing, human pose estimation, and weather forecasting. Current research focuses on improving motion vector estimation accuracy and efficiency, particularly through deep learning models such as vision transformers and convolutional neural networks, often incorporating auxiliary data like depth or edge information to handle complex motions and occlusions. These advancements have significant implications for enhancing video quality (e.g., frame interpolation, super-resolution), improving human-computer interaction through more accurate emotion recognition, and advancing meteorological predictions via more precise atmospheric motion analysis.