What do I see? Modeling human visual perception for multi-person tracking

Xu Yan, Ioannis A. Kakadiaris, Shishir K. Shah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


This paper presents a novel approach for multi-person tracking utilizing a model motivated by the human vision system. The model predicts human motion based on modeling of perceived information. An attention map is designed to mimic human reasoning that integrates both spatial and temporal information. The spatial component addresses human attention allocation to different areas in a scene and is represented using a retinal mapping based on the log-polar transformation while the temporal component denotes the human attention allocation to subjects with different motion velocity and is modeled as a static-dynamic attention map. With the static-dynamic attention map and retinal mapping, attention driven motion of the tracked target is estimated with a center-surround search mechanism. This perception based motion model is integrated into a data association tracking framework with appearance and motion features. The proposed algorithm tracks a large number of subjects in complex scenes and the evaluation on public datasets show promising improvements over state-of-the-art methods.

Original languageEnglish (US)
Title of host publicationComputer Vision, ECCV 2014 - 13th European Conference, Proceedings
Number of pages16
EditionPART 2
ISBN (Print)9783319106045
StatePublished - 2014
Event13th European Conference on Computer Vision, ECCV 2014 - Zurich, Switzerland
Duration: Sep 6 2014Sep 12 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume8690 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference13th European Conference on Computer Vision, ECCV 2014

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


Dive into the research topics of 'What do I see? Modeling human visual perception for multi-person tracking'. Together they form a unique fingerprint.

Cite this