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Spatio-temporal prediction of collision candidates for static and dynamic objects in monocular image sequences

Schaub, Alexander and Burschka, Darius (2013) Spatio-temporal prediction of collision candidates for static and dynamic objects in monocular image sequences. Intelligent Vehicles Symposium (IV), 2013 IEEE, Gold Coast Australien. ISBN 978-1-4673-2754-1 ISSN 1931-0587

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Abstract

This paper presents a novel approach for reactive obstacle avoidance for static and dynamic objects using monocular image sequences. A sparse motion field is calculated by tracking point features using the Kanade-Lucas-Tomasi method. The rotational component of this sparse optical flow due to ego motion of the camera is compensated using motion parameters estimated directly from the images. A robust method for detection of static and dynamic objects in the scene is applied to identify collision candidates. The approach operates entirely in the image space of a monocular camera and does not require any extrinsic information about the configuration of the sensor or speed of the camera. The system prioritizes the detected collision candidates by their time to collision. Additionally, the spatial distribution of the candidates is calculated for non-degenerated conditions. We present the mathematical framework and the experimental validation of the suggested approach on simulated and real-world data.

Item URL in elib:https://elib.dlr.de/85482/
Document Type:Conference or Workshop Item (Poster)
Title:Spatio-temporal prediction of collision candidates for static and dynamic objects in monocular image sequences
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Schaub, Alexanderalexander.schaub (at) dlr.deUNSPECIFIED
Burschka, Dariusburschka (at) cs.tum.deUNSPECIFIED
Date:June 2013
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Page Range:pp. 1052-1058
ISSN:1931-0587
ISBN:978-1-4673-2754-1
Status:Published
Keywords:collision avoidance; image motion analysis; image sensors; image sequences; mobile robots; parameter estimation; remotely operated vehicles; robot vision; Kanade-Lucas-Tomasi method; camera ego motion; collision candidates spatio-temporal prediction; dynamic objects; monocular camera; monocular image sequences; motion parameters estimation; reactive obstacle avoidance; sparse motion field; sparse optical flow; static objects; Adaptive optics; Cameras;Collision avoidance; Optical imaging; Optical sensors; Robot sensing systems;
Event Title:Intelligent Vehicles Symposium (IV), 2013 IEEE
Event Location:Gold Coast Australien
Event Type:international Conference
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - Project RMC - Aufbau (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of System Dynamics and Control > Vehicle System Dynamics
Deposited By: Schaub, Alexander
Deposited On:22 Nov 2013 10:27
Last Modified:07 Sep 2016 11:12

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