Tightly integrated sensor fusion for robust visual tracking

被引：32

作者：

Klein, GSW ^{[1
]}

Drummond, TW ^{[1
]}

机构：

[1] Univ Cambridge, Dept Engn, Cambridge CB1 2PZ, England

来源：

IMAGE AND VISION COMPUTING | 2004年 / 22卷 / 10期

关键词：

visual tracking; real-time vision; sensor fusion;

D O I：

10.1016/j.imavis.2004.02.007

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a novel method for increasing the robustness of visual tracking systems by incorporating information from inertial sensors. We show that more can be achieved than simply combining the sensor data within a statistical filter: besides using inertial data to provide predictions for the visual sensor, this data can be used to dynamically tune the parameters of each feature detector in the visual sensor. This allows the visual sensor to provide useful information even in the presence of substantial motion blur. Finally, the visual sensor can be used to calibrate the parameters of the inertial sensor to eliminate drift. (C) 2004 Elsevier B.V. All rights reserved.

引用

页码：769 / 776

页数：8

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