Facilitating fashion camouflage art

  title={Facilitating fashion camouflage art},
  author={Ranran Feng and B. Prabhakaran},
  journal={Proceedings of the 21st ACM international conference on Multimedia},
  • Ranran FengB. Prabhakaran
  • Published 21 October 2013
  • Art, Computer Science
  • Proceedings of the 21st ACM international conference on Multimedia
Artists and fashion designers have recently been creating a new form of art -- Camouflage Art -- which can be used to prevent computer vision algorithms from detecting faces. [] Key Method This tool can find the prominent or decisive features from facial images that constitute the face being recognized; and give suggestions for camouflage options (makeup, styling, paints) on particular facial features or facial parts. Testing of this tool shows that it can effectively aid the artists or designers in creating…

Challenges in Face Recognition Using Machine Learning Algorithms: Case of Makeup and Occlusions

It is shown that the makeup and other occlusions can be used not only to disguise a person’s identity from the ANN algorithms, but also to spoof a wrong identification.

Mapping the emotional face. How individual face parts contribute to successful emotion recognition

A similarity analysis of the usefulness of different face parts for expression recognition demonstrated that faces cluster according to the emotion they express, rather than by low-level physical features.

SoK: Anti-Facial Recognition Technology

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BiometricJammer: Method to Prevent Acquisition of Biometric Information by Surreptitious Photography on Fingerprints

It is demonstrated that an implementation of the proposed method called “BiometricJammer,” a wearable device put on a fingertip, can effectively prevent the illegal acquisition of fingerprints by surreptitious photography while still enabling contact-based fingerprint sensors to respond normally.

Accessorize to a Crime: Real and Stealthy Attacks on State-of-the-Art Face Recognition

A novel class of attacks is defined: attacks that are physically realizable and inconspicuous, and allow an attacker to evade recognition or impersonate another individual, and a systematic method to automatically generate such attacks is developed through printing a pair of eyeglass frames.

A white-box impersonation attack on the FaceID system in the real world

A mask sticker attack method to realize the impersonation attack of arcface model that specifically uses a parabolic transformation to simulate the bending situation of a sticker on a mask, and uses a multi-stage PGD attack to generate a adversarial sticker.

Deep Gradient Learning for Efficient Camouflaged Object Detection

DGNet is a novel deep framework that exploits object gradient supervision for camouflaged object detection (COD) and outperforms existing state-of-the-art COD models by a large margin.

Adversarial Image Translation: Unrestricted Adversarial Examples in Face Recognition Systems

This work proposes a flexible and efficient method for generating unrestricted adversarial examples using image translation techniques that enables it to translate a source image into any desired facial appearance with large perturbations to deceive target face recognition systems.

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We investigate whether the well-known poor performance of the head-on usage of the convolutional neural networks for the facial expression recognition task may be improved in terms of reducing the

Robust Synthesis of Adversarial Visual Examples Using a Deep Image Prior

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The Makeup Artist Handbook: Techniques for Film, Television, Photography, and Theatre

This full-color and amply illustrated book is written for film, television, and theatre makeup artists who need to know the basics on how to accomplish flawless makeup applications. It begins with

Face recognition with disguise and single gallery images

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Robust Real-Time Face Detection

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Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection

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FRVT 2006 and ICE 2006 large-scale results

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Feature-based face recognition using mixture-distance

  • I. CoxJ. GhosnP. Yianilos
  • Computer Science
    Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition
  • 1996
The results demonstrate that even in the absence of multiple training examples for each class, it is sometimes possible to infer from a statistical model of training data, a significantly improved distance function for use in pattern recognition.