Dynamic Phase and Group Detection in Pedestrian Crowd Data Using Multiplex Visibility Graphs | Zendy

C. Arul Stephen | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Dynamic Phase and Group Detection in Pedestrian Crowd Data Using Multiplex Visibility Graphs

Author(s) -

C. Arul Stephen

Publication year - 2015

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2015.07.318

Subject(s) - computer science , pedestrian , multiplex , cluster analysis , visibility , graph , simple (philosophy) , artificial intelligence , data mining , theoretical computer science , bioinformatics , philosophy , epistemology , biology , physics , optics , transport engineering , engineering

We study pedestrian crowd dynamics and the detection of groups in a scene. We propose a novel method to analyse pedestrian trajectories by translating them to multiplex networks, whose properties can be studied using the tools of graph theory. Our results show that simple measures on the resulting multiplex graphs accurately reflect both the global dynamics and local clustering within scenes

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research