Abstract: Described herein are computerized methods and systems for detecting fraud during biometric identity verification. A mobile device captures video comprising a plurality of frames of a person's face. The mobile device extracts from the video frames comprising at least two frames of the person's face from different angles. The mobile device creates a reconstruction of the person's face using the extracted frames and derives signals associated with features of the person's face. The mobile device generates an embedding for each extracted frame using the extracted frames, the three-dimensional reconstruction, and the signals. The mobile device calculates, for each extracted frame, a fraud confidence value based upon the embedding for the extracted frame, attributes of the person's face, and image quality attributes of the extracted image. The mobile device computes a fraud detection decision for the extracted frames based upon the fraud confidence values and the embeddings.

Abstract: Described herein are computerized methods and systems for detecting fraud during biometric identity verification. A mobile device captures video comprising a plurality of frames of a person's face. The mobile device extracts from the video frames comprising at least two frames of the person's face from different angles. The mobile device creates a reconstruction of the person's face using the extracted frames and derives signals associated with features of the person's face. The mobile device generates an embedding for each extracted frame using the extracted frames, the three-dimensional reconstruction, and the signals. The mobile device calculates, for each extracted frame, a fraud confidence value based upon the embedding for the extracted frame, attributes of the person's face, and image quality attributes of the extracted image. The mobile device computes a fraud detection decision for the extracted frames based upon the fraud confidence values and the embeddings.