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

Aiming to address the fast multi-object tracking for dense small object inthe cluster background, we review track orientated multi-hypothesistracking(TOMHT) with consideration of batch optimization. Employingautocorrelation based motion score test and staged hypotheses merging approach,we build our homologous hypothesis generation and management method. A newone-to-many constraint is proposed and applied to tackle the track exclusionsduring complex occlusions. Besides, to achieve better results, we develop amulti-appearance segmentation for detection, which exploits tree-liketopological information and realizes one threshold for one object. Experimentalresults verify the strength of our methods, indicating speed and performanceadvantages of our tracker.

Multi-appearance Segmentation and Extended 0-1 Program for Dense Small Object Tracking