by Morales, S and Klette, R
Abstract:
Using image sequences as input for vision-based algorithms allows the possibility of merging information from previous images into the analysis of the current image. In the context of video-based driver assistance systems, such temporal analysis can lead to the improvement of depth estimation of visible objects. This paper presents a Kalman filter-based approach that focuses on the reduction of uncertainty in disparity maps of image sequences. For each pixel in the current disparity map, we incorporate disparity data from neighbourhoods of corresponding pixels in the immediate previous and the current image frame. Similar approaches have been considered before that also use disparity information from previous images, but without complementing the analysis with data from neighbouring pixels. © 2011 Springer-Verlag.
Reference:
Spatio-temporal stereo disparity integration (Morales, S and Klette, R), In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 6855 LNCS, 2011.
Bibtex Entry:
@inproceedings{morales2011spatio-temporalintegration,
author = "Morales, S and Klette, R",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "540--547",
title = "Spatio-temporal stereo disparity integration",
volume = "6855 LNCS",
year = "2011",
abstract = "Using image sequences as input for vision-based algorithms allows the possibility of merging information from previous images into the analysis of the current image. In the context of video-based driver assistance systems, such temporal analysis can lead to the improvement of depth estimation of visible objects. This paper presents a Kalman filter-based approach that focuses on the reduction of uncertainty in disparity maps of image sequences. For each pixel in the current disparity map, we incorporate disparity data from neighbourhoods of corresponding pixels in the immediate previous and the current image frame. Similar approaches have been considered before that also use disparity information from previous images, but without complementing the analysis with data from neighbouring pixels. © 2011 Springer-Verlag.",
doi = "10.1007/978-3-642-23678-5_64",
isbn = "9783642236778",
issn = "0302-9743",
eissn = "1611-3349",
issue = "PART 2",
keyword = "disparity map",
keyword = "driver assistance",
keyword = "Kalman filter",
keyword = "stereo analysis",
keyword = "temporal propagation",
language = "eng",
}