English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Face identity masking algorithms developed in recent years aim to protect theprivacy of people in video recordings. These algorithms are designed tointerfere with identification, while preserving information about facialactions. An important challenge is to preserve subtle actions in the eyeregion, while obscuring the salient identity cues from the eyes. We evaluatedthe effectiveness of identity-masking algorithms based on Canny filters,applied with and without eye enhancement, for interfering with identificationand preserving facial actions. In Experiments 1 and 2, we tested humanparticipants' ability to match the facial identity of a driver in a lowresolution video to a high resolution facial image. Results showed that bothmasking methods impaired identification, and that eye enhancement did not alterthe effectiveness of the Canny filter mask. In Experiment 3, we tested actionpreservation and found that neither method interfered significantly with driveraction perception. We conclude that relatively simple, filter-based maskingalgorithms, which are suitable for application to low quality video, can beused in privacy protection without compromising action perception.

Identity masking effectiveness and gesture recognition: Effects of eye enhancement in seeing through the mask