by Sánchez, JA, Klette, R and Destefanis, E
Abstract:
This paper proposes a technique for estimating 3D flow vectors, by combining a KLT tracker with subsequent scale-space analysis of tracked points. A tracked point defines a 2D vector, which is mapped into 3D space based on ratios of maxima of scale-space characteristics. The approach is tested for night-vision sequences as recorded (at Daimler AG, Germany) for driver assistance projects. Those image sequences (at 25Hz) are characterized by being slightly blurry and of low contrast. © 2009 Springer Berlin Heidelberg.
Reference:
Estimating 3D flow for driver assistance applications (Sánchez, JA, Klette, R and Destefanis, E), In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 5414 LNCS, 2009.
Bibtex Entry:
@inproceedings{snchez2009estimatingapplications,
author = "Sánchez, JA and Klette, R and Destefanis, E",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "237--248",
title = "Estimating 3D flow for driver assistance applications",
volume = "5414 LNCS",
year = "2009",
abstract = "This paper proposes a technique for estimating 3D flow vectors, by combining a KLT tracker with subsequent scale-space analysis of tracked points. A tracked point defines a 2D vector, which is mapped into 3D space based on ratios of maxima of scale-space characteristics. The approach is tested for night-vision sequences as recorded (at Daimler AG, Germany) for driver assistance projects. Those image sequences (at 25Hz) are characterized by being slightly blurry and of low contrast. © 2009 Springer Berlin Heidelberg.",
doi = "10.1007/978-3-540-92957-4_21",
issn = "0302-9743",
eissn = "1611-3349",
keyword = "3D motion",
keyword = "Driver assistance",
keyword = "Motion analysis",
keyword = "Motion vector fields",
language = "eng",
}