TITLE

Filtering Based Adaptive Visual Odometry Sensor Framework Robust to Blurred Images

AUTHOR(S)
Haiying Zhao; Yong Liu; Xiaojia Xie; Liao, Yiyi; Xixi Liu
PUB. DATE
July 2016
SOURCE
Sensors (14248220);Jul2016, Vol. 16 Issue 7, p1040
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Visual odometry (VO) estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estimation from blurred images, and present an adaptive visual odometry estimation framework robust to blurred images. Our approach employs an objective measure of images, named small image gradient distribution (SIGD), to evaluate the blurring degree of the image, then an adaptive blurred image classification algorithm is proposed to recognize the blurred images, finally we propose an anti-blurred key-frame selection algorithm to enable the VO robust to blurred images. We also carried out varied comparable experiments to evaluate the performance of the VO algorithms with our anti-blur framework under varied blurred images, and the experimental results show that our approach can achieve superior performance comparing to the state-of-the-art methods under the condition with blurred images while not increasing too much computation cost to the original VO algorithms.
ACCESSION #
120514889

 

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