Abstract: A cascade auto-review system for automated classification and annotation of input is provided. An example system is structure adaptive and task oriented and includes a communication module configured to receive the input including images, videos, and metadata. The system further includes a plurality of subsystems. Each subsystem has a series of successive classifier stages configured to detect tags in the input and approve or reject the tags based on the images, the videos, and the metadata. The system further includes a database to store results of the classification and annotation. The results are used to train computer vision and machine learning algorithms.

Abstract: A system may monitor social media sites for posts comprising brand indicia and collect analytics data related to the posts. Brand exposure may be quantified based on the analytics data.

Abstract: An image identification system may identify key points on a known image and an unidentified image. One or more geometric shapes may be formed from the key points. A match between the unidentified image and the know image nay be determined by comparison of the respective geometric shapes.

Abstract: An image identification system may identify key points on a known image, variations of the known image in different levels of blur, and an unidentified image. One or more geometric shapes may be formed from the key points. A match between the unidentified image and either the known image or a blurred variation of the known image may be determined by comparison of the respective geometric shapes.