Recognizing People by Their Personal Aesthetics:
A New Soft Biometric Trait

This work builds upon the belief that every human being has a built-in image aesthetic evaluation system. This sort of “personal aesthetics” mostly follows certain aesthetic rules widely studied in image aesthetics (e.g., rules of thirds, colorfulness, etc.) though it likely contains some innate, unique preferences. This work is a proof of concept of this intuition, presenting personal aesthetics as a novel behavioral biometrical trait. In our scenario, personal aesthetics activate when an individual is presented with a set of photos he may like or dislike: the goal is to distill and encode the uniqueness of his visual preferences into a compact template. To this aim, we extract a pool of low- and high-level state-of-the-art image features from a set of Flickr images preferred by a user, feeding them successively into a LASSO regressor. LASSO highlights the most discriminant cues for the individual, allowing authentication and recognition tasks. The results are surprising: given only 1 image as test, we can match the user identity against a gallery of 200 individuals definitely much better than chance; using 20 images (all preferred by a single user) as a biometrical trait, we reach an AUC of 96%, considering the Cumulative Matching Characteristic curve. Extensive experiments also support the interpretability of our approach, effectively modelling what is the “what we like” which distinguishes us from the others.


 

Papers

2014
P. Lovato, M. Bicego, C. Segalin, A. Perina, N. Sebe and M. Cristani
Faved! Biometrics: Tell Me Which Image You Like and I'll Tell You Who You Are
IEEE Transactions on Information Forensics, pp. 364-374, 2014
pdf
C. Segalin, A. Perina and M. Cristani
Biometrics on Visual Preferences: a "Pump and Distill" Regression Approach
IEEE International Conference on Image Processing (ICIP), 2014
pdf, poster
C. Segalin, A. Perina and M. Cristani
Recognizing People by Their Personal Aesthetics: a Statistical Multi-level Approach
The 12th Asian Conference on Computer Vision (ACCV), 2014
pdf, poster
C. Segalin, A. Perina and M. Cristani
Personal Aesthetics for Soft Biometrics: a Generative Multiresolution Approach
The 16th International Conference on Multimodal Interaction (ICMI), 2014
pdf, supp mat, poster

Data


Download the dataset here: Dataset_IEEEForensics.zip. This dataset includes 40000 images, 200 favorite images for each of the 200 users selected from Flickr. We also provide the feature matrix of the features extracted form the dataset.
Please cite the first paper if you use this dataset.
Last Update August 2016