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

In this paper, we present a data-driven approach for human pose tracking invideo data. We formulate the human pose tracking problem as a discreteoptimization problem based on spatio-temporal pictorial structure model andsolve this problem in a greedy framework very efficiently. We propose the modelto track the human pose by combining the human pose estimation from singleimage and traditional object tracking in a video. Our pose tracking objectivefunction consists of the following terms: likeliness of appearance of a partwithin a frame, temporal displacement of the part from previous frame to thecurrent frame, and the spatial dependency of a part with its parent in thegraph structure. Experimental evaluation on benchmark datasets (VideoPose2,Poses in the Wild and Outdoor Pose) as well as on our newly build ICDPosedataset shows the usefulness of our proposed method.

A Data-driven Approach for Human Pose Tracking Based on Spatio-temporal Pictorial Structure