Robust False Positive Detection for Real-Time Multi-target Tracking

Brauer, Henrik, Grecos, Christos and von Luck, Kai (2014) Robust False Positive Detection for Real-Time Multi-target Tracking. In: Image and Signal Processing. ICISP 2014. Lecture Notes in Computer Science (8509). Springer, Cham, pp. 450-459. ISBN 9783319079981

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Abstract

We present a real-time multi-target tracking system that effectively deals with false positive detections. In order to achieve this, we build a novel motion model that treats false positives on background objects and false positives on foreground objects such as shoulders or bags separately. In addition we train a new head detector based on the Aggregated Channel Features (ACF) detector and propose a schema that includes the identification of true positives with the data association instead of using the internal decision-making process of the detector. Through several experiments, we show that our system is superior to previous work.

Item Type:	Book Section
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software
Divisions:	School of Computing > Staff Research and Publications
Depositing User:	Caoimhe Ní Mhaicín
Date Deposited:	04 Mar 2019 14:04
Last Modified:	04 Mar 2019 14:04
URI:	https://norma.ncirl.ie/id/eprint/3640

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