Autonomous video registration using sensor model parameter adjustments

Cannata, Richard; Shah, Mubarak; Blask, Steven; Workum, J.A. Van

doi:10.1109/aiprw.2000.953628

Cited by 17 publications

(11 citation statements)

References 2 publications

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“…In a geo-registration system (GRS), digital image registration [1] is a crucial task to accurately establish the relative position of a live image captured by a camera in a large reference image [2][3][4][5][9] [10]. The main objective of a video-based GRS is to determine the geo-location, i.e.…”

Section: Introductionmentioning

confidence: 99%

Improving robustness of real-time geo-registration process

Linh

Satzoda

Suchitra

et al. 2008

2008 International Conference on Neural Networks and Signal Processing

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In this paper, a modified correspondence matching method is proposed for geo-registration system that enables parallelism and image update detection. The image to be geo-referenced is divided into blocks which can be processed in parallel. A voting process is performed on the correlation measures obtained from different blocks to determine the match point. An image update detection method is also presented, which uses the correlation data from the proposed block based matching method to determine which parts of the image have been updated or changed with respect to an existing reference image. The experimental results to evaluate the proposed methods are presented. The proposed method gives better matching scores compared to the conventional correlation approach.

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Section: Introductionmentioning

confidence: 99%

Improving robustness of real-time geo-registration process

Linh

Satzoda

Suchitra

et al. 2008

2008 International Conference on Neural Networks and Signal Processing

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“…A similar scenario has been presented in [1]. In area based matching, MSE [6] or normalized correlation [3] are used to determine correspondences between the UAV image and the reference image. However, the UAV images are captured at different times and in different views with respect to the satellite image.…”

Section: Introductionmentioning

confidence: 99%

Map-Enhanced UAV Image Sequence Registration and Synchronization of Multiple Image Sequences

Lin

Medioni

2007

2007 IEEE Conference on Computer Vision and Pattern Recognition

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“…Visual navigation techniques enhance the reliability and robustness of GNSS/IMU. They improve the pose parameters by measuring features in the environment and comparing them with a database (Kumar et al 1998;Cannata et al 2000;Wildes et al 2001;Sim et al 2002;Samadzadegan et al 2007;Conte & Doherty 2009;Saeedi et al 2009;Kamel et al 2010;Sheta 2012;Hwangbo 2012;Sanfourche et al 2012;Lee et al 2013). However, the visual navigation techniques require an initialization with an approximate position solution in order to minimize the computational load and the number of ambiguities.…”

Section: Introductionmentioning

confidence: 99%

Pose Estimation of Unmanned Aerial Vehicles Based on a Vision-Aided Multi-Sensor Fusion

Abdi¹,

Samadzadegan²,

Kurz³

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:GNSS/IMU navigation systems offer low-cost and robust solution to navigate UAVs. Since redundant measurements greatly improve the reliability of navigation systems, extensive researches have been made to enhance the efficiency and robustness of GNSS/IMU by additional sensors. This paper presents a method for integrating reference data, images taken from UAVs, barometric height data and GNSS/IMU data to estimate accurate and reliable pose parameters of UAVs. We provide improved pose estimations by integrating multi-sensor observations in an EKF algorithm with IMU motion model. The implemented methodology has demonstrated to be very efficient and reliable for automatic pose estimation. The calculated position and attitude of the UAV especially when we removed the GNSS from the working cycle clearly indicate the ability of the purposed methodology.

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Autonomous video registration using sensor model parameter adjustments

Cited by 17 publications

References 2 publications

Improving robustness of real-time geo-registration process

Improving robustness of real-time geo-registration process

Map-Enhanced UAV Image Sequence Registration and Synchronization of Multiple Image Sequences

Pose Estimation of Unmanned Aerial Vehicles Based on a Vision-Aided Multi-Sensor Fusion

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