Benchmarking Human Face Similarity Using Identical Twins

by   Shoaib Meraj Sami, et al.

The problem of distinguishing identical twins and non-twin look-alikes in automated facial recognition (FR) applications has become increasingly important with the widespread adoption of facial biometrics. Due to the high facial similarity of both identical twins and look-alikes, these face pairs represent the hardest cases presented to facial recognition tools. This work presents an application of one of the largest twin datasets compiled to date to address two FR challenges: 1) determining a baseline measure of facial similarity between identical twins and 2) applying this similarity measure to determine the impact of doppelgangers, or look-alikes, on FR performance for large face datasets. The facial similarity measure is determined via a deep convolutional neural network. This network is trained on a tailored verification task designed to encourage the network to group together highly similar face pairs in the embedding space and achieves a test AUC of 0.9799. The proposed network provides a quantitative similarity score for any two given faces and has been applied to large-scale face datasets to identify similar face pairs. An additional analysis which correlates the comparison score returned by a facial recognition tool and the similarity score returned by the proposed network has also been performed.


page 3

page 13

page 14

page 24

page 25

page 26

page 27

page 28


Finding your Lookalike: Measuring Face Similarity Rather than Face Identity

Face images are one of the main areas of focus for computer vision, rece...

Deep Face Quality Assessment

Face image quality is an important factor in facial recognition systems ...

A Linked Aggregate Code for Processing Faces (Revised Version)

A model of face representation, inspired by the biology of the visual sy...

Reliable Detection of Doppelgängers based on Deep Face Representations

Doppelgängers (or lookalikes) usually yield an increased probability of ...

Twin identification over viewpoint change: A deep convolutional neural network surpasses humans

Deep convolutional neural networks (DCNNs) have achieved human-level acc...

On the Perception of Small Sub-graphs

Interpreting a node-link graph is enhanced if similar subgraphs (or moti...

2-gram-based Phonetic Feature Generation for Convolutional Neural Network in Assessment of Trademark Similarity

A trademark is a mark used to identify various commodities. If same or s...

Please sign up or login with your details

Forgot password? Click here to reset