Template Matching

Template matching, a fundamental computer vision technique, aims to identify instances of a known template within a larger image or video. Current research focuses on improving efficiency and robustness, particularly for high-resolution data and challenging scenarios like occlusions, varying illumination, and non-rigid transformations. This involves developing novel algorithms, such as tensorial template matching for faster rotation handling and adaptive template matching for tracking dynamic objects, often incorporating deep learning architectures like convolutional neural networks and vision transformers. The advancements in template matching have significant implications across diverse fields, including medical image analysis, industrial automation, and autonomous systems.