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

Micro-expression can reflect people's real emotions. Recognizingmicro-expressions is difficult because they are small motions and have a shortduration. As the research is deepening into micro-expression recognition, manyeffective features and methods have been proposed. To determine which directionof movement feature is easier for distinguishing micro-expressions, this paperselects 18 directions (including three types of horizontal, vertical andoblique movements) and proposes a new low-dimensional feature called theHistogram of Single Direction Gradient (HSDG) to study this topic. In thispaper, HSDG in every direction is concatenated with LBP-TOP to obtain the LBPwith Single Direction Gradient (LBP-SDG) and analyze which direction ofmovement feature is more discriminative for micro-expression recognition. Aswith some existing work, Euler Video Magnification (EVM) is employed as apreprocessing step. The experiments on the CASME II and SMIC-HS databasessummarize the effective and optimal directions and demonstrate that HSDG in anoptimal direction is discriminative, and the corresponding LBP-SDG achievesstate-of-the-art performance using EVM.

A comparative study on movement feature in different directions for micro-expression recognition