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

Determining the direction in which a person is looking is an importantproblem in a wide range of HCI applications. In this paper we describe a highlyaccurate algorithm that performs gaze estimation using an affordable and widelyavailable device such as Kinect. The method we propose starts by performingaccurate head pose estimation achieved by fitting a person specific morphablemodel of the face to depth data. The ordinarily competing requirements of highaccuracy and high speed are met concurrently by formulating the fittingobjective function as a combination of terms which excel either in accurate orfast fitting, and then by adaptively adjusting their relative contributionsthroughout fitting. Following pose estimation, pose normalization is done byre-rendering the fitted model as a frontal face. Finally gaze estimates areobtained through regression from the appearance of the eyes in synthetic,normalized images. Using EYEDIAP, the standard public dataset for theevaluation of gaze estimation algorithms from RGB-D data, we demonstrate thatour method greatly outperforms the state of the art.

Highly accurate gaze estimation using a consumer RGB-depth sensor