Local features are extracted from the input frame and matched with a candidate target in the database. The RANSAC [1] algorithm is used to detect feature outliers. In particular, it is composed of two main parts: recognition of the painting from the dataset with a SIFT-based approach, and temporal and spatial reasoning to obtain a robust detection.