Global localization and relative positioning based on scale-invariant keypoints

Košecká, Jana; Li, Fayin; Yang, Xiaolong

doi:10.1016/j.robot.2005.03.008

Cited by 91 publications

(73 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Following a similar approach, but in a non-incremental perspective, voting methods presented in [14] and [15] call upon maximum likelihood estimation to match the current image with a database of images acquired beforehand. The likelihood depends upon the number of feature correspondences between the images, and leads to a vote assessing the amount of similarity.…”

Section: Related Workmentioning

confidence: 99%

“…The likelihood depends upon the number of feature correspondences between the images, and leads to a vote assessing the amount of similarity. In [14], the authors also use multipleview geometry to validate each matching hypothesis, while in [15] the accuracy of the likelihood is qualitatively evaluated in order to reject outliers. Even though they are easy to implement, voting methods rely on an offline construction of the image database and need expensive one-to-one image comparisons when searching for the most likely hypotheses.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Real-time visual loop-closure detection

Angeli

Doncieux

Meyer

et al. 2008

2008 IEEE International Conference on Robotics and Automation

View full text Add to dashboard Cite

Abstract-In robotic applications of visual simultaneous localization and mapping, loop-closure detection and global localization are two issues that require the capacity to recognize a previously visited place from current camera measurements. We present an online method that makes it possible to detect when an image comes from an already perceived scene using local shape information. Our approach extends the bag of visual words method used in image recognition to incremental conditions and relies on Bayesian filtering to estimate loopclosure probability. We demonstrate the efficiency of our solution by real-time loop-closure detection under strong perceptual aliasing conditions in an indoor image sequence taken with a handheld camera.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Real-time visual loop-closure detection

Angeli

Doncieux

Meyer

et al. 2008

2008 IEEE International Conference on Robotics and Automation

View full text Add to dashboard Cite

show abstract

“…For the planar sea floor of this experiment, a monocular two-dimensional setup is used. The visual odometer estimates robot motion and pose from image features that can be well localized and that are relatively invariant to contrast, scale, and view point [20][21][22]. The type of features that gives best results depends on the type of scene and can be adapted during a mission, though we find that in natural environments blobs-round areas with high contrast against the background-give more reliable estimates than edges and lines.…”

Section: The Vision Module Architecturementioning

confidence: 99%

Reconfigurable AUV for intervention missions: a case study on underwater object recovery

Prats

Ribas

Palomeras

et al. 2011

Intel Serv Robotics

View full text Add to dashboard Cite

Starting in January 2009, the RAUVI (Reconfigurable Autonomous Underwater Vehicle for Intervention Missions) project is a three years coordinated research action funded by the Spanish Ministry of Research and Innovation. In this paper, the state of progress after two years of continuous research is reported. As a first experimental validation of the complete system, a Search & Recovery problem is addressed, consisting of finding and recovering a flight data recorder placed at an unknown position at the bottom of a water tank. An overview of the techniques used to successfully solve the problem in an autonomous way is provided. The obtained results are very promising and are the first step toward the final test in shallow water at the end of 2011.

show abstract

“…A more proper solution is proposed by Brooks [21] which formulates a least square approach to the planar relative pose given noise free correspondences. This result was used in [22,23,2] for various robotics applications all in combination with RANSAC. In [22,24] it was shown that two correspondences are enough to solve the problem and both suggest algorithms, which are briefly evaluated in combination with RANSAC.…”

Section: Introductionmentioning

confidence: 99%

Efficient probabilistic planar robot motion estimation given pairs of images

Booij¹,

Kröse²,

Zivkovic³

2010

Robotics: Science and Systems VI

View full text Add to dashboard Cite

Abstract-Estimating the relative pose between two camera positions given image point correspondences is a vital task in most view based SLAM and robot navigation approaches. In order to improve the robustness to noise and false point correspondences it is common to incorporate the constraint that the robot moves over a planar surface, as is the case for most indoor and outdoor mapping applications. We propose a novel estimation method that determines the full likelihood in the space of all possible planar relative poses. The likelihood function can be learned from existing data using standard Bayesian methods and is efficiently stored in a low dimensional look up table. Estimating the likelihood of a new pose given a set of correspondences boils down to a simple look up. As a result, the proposed method allows for very efficient creation of pose constraints for vision based SLAM applications, including a proper estimate of its uncertainty. It can handle ambiguous image data, such as acquired in long corridors, naturally. The method can be trained using either artificial or real data, and is applied on both controlled simulated data and challenging images taken in real home environments. By computing the maximum likelihood estimate we can compare our approach with state of the art estimators based on a combination of RANSAC and iterative reweighted least squares and show a significant increase in both the efficiency and accuracy.

show abstract

Global localization and relative positioning based on scale-invariant keypoints

Cited by 91 publications

References 24 publications

Real-time visual loop-closure detection

Real-time visual loop-closure detection

Reconfigurable AUV for intervention missions: a case study on underwater object recovery

Efficient probabilistic planar robot motion estimation given pairs of images

Contact Info

Product

Resources

About