Spoofing 2D Face Detection: Machines See People Who Aren't There

08/06/2016
by   Michael McCoyd, et al.
0

Machine learning is increasingly used to make sense of the physical world yet may suffer from adversarial manipulation. We examine the Viola-Jones 2D face detection algorithm to study whether images can be created that humans do not notice as faces yet the algorithm detects as faces. We show that it is possible to construct images that Viola-Jones recognizes as containing faces yet no human would consider a face. Moreover, we show that it is possible to construct images that fool facial detection even when they are printed and then photographed.

READ FULL TEXT

page 3

page 5

page 6

page 8

research
10/12/2019

Spoofing and Anti-Spoofing with Wax Figure Faces

We have witnessed rapid advances in both face presentation attack models...
research
05/05/2017

Learning to see people like people

Humans make complex inferences on faces, ranging from objective properti...
research
06/29/2022

Convolutional Neural Network Based Partial Face Detection

Due to the massive explanation of artificial intelligence, machine learn...
research
05/15/2018

On Learning Associations of Faces and Voices

In this paper, we study the associations between human faces and voices....
research
08/04/2020

FaceOff: Detecting Face Touching with a Wrist-Worn Accelerometer

According to the CDC, one key step of preventing oneself from contractin...
research
03/30/2021

Face Forensics in the Wild

On existing public benchmarks, face forgery detection techniques have ac...
research
10/30/2017

Can you find a face in a HEVC bitstream?

Finding faces in images is one of the most important tasks in computer v...

Please sign up or login with your details

Forgot password? Click here to reset