Authors:
Saira Saleem Pathan
1
;
Ayoub Al-Hamadi
1
;
Gerald Krell
2
and
Bernd Michaelis
2
Affiliations:
1
Institute for Electronics, Signal Processing and Communications (IESK), Otto-von-Guericke-University Magdeburg, Germany
;
2
Otto-von-Guericke University of Magdeburg, Germany
Keyword(s):
Multi-object tracking, Data Association, Logical Reasoning, Motion Analysis.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Human-Computer Interaction
;
Image and Video Analysis
;
Methodologies and Methods
;
Motion and Tracking
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Physiological Computing Systems
;
Software Engineering
;
Video Analysis
Abstract:
In real-time tracking, a crucial challenge is to efficiently build association among the objects. However, real-time interferences~(e.g. occlusion) manifest errors in data association. In this paper, the uncertainties in data association are handled when discrete information is incomplete during occlusion through qualitative reasoning modules. The formulation of the qualitative modules are based on exploiting human-tracking abilities (i.e. common sense) which are integrated with data association technique. Each detected object is described as a node in space with a unique identity and status tag whereas association weights are computed using CWHI and Bhattacharyya coefficient. These weights are input to qualitative modules which interpret the appropriate status of the objects satisfying the fundamental constraints of object's continuity during tracking. The results are linked with Kalman Filter to estimate the trajectories of objects. The proposed approach has shown promising result
s illustrating its contribution when tested on a set of videos representing various challenges.
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