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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We present a new framework for robust 3D tracking, using a dynamic data driven coupling of continuous and discrete methods to overcome their limitations. Our method uses primarily the continuous-based tracking which is replaced by the discrete one, to obtain model re-initializations when necessary. We use the error in the continuous tracking to learn off-line, based on SVMs, when the continuous-based tracking fails and switch between the two methods. We develop a novel discrete method for 3D shape configuration estimation, which utilizes both frame and multi-frame features, taking into account the most recent input frames, using a time-window. We therefore overcome the error accumulation over time, that most continuous methods suffer from and simultaneously reduce the discrete method's complexity and prevent possible multiple solutions in shape estimation. We demonstrate the power of our framework in complex hand tracking sequences with large rotations, articulations, lighting changes and occlusions.

Dynamic Data Driven Coupling of Continuous and Discrete Methods for 3D Tracking