Robust and Efficient Pose Estimation from Line Correspondences

Zhang, Lilian; Xu, Chi; Lee, Kok-Meng; Koch, Reinhard

doi:10.1007/978-3-642-37431-9_17

Cited by 55 publications

(39 citation statements)

References 17 publications

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“…The redundancy of data is increased by expressing the correspondences in two coordinate systems, Euclidean and Plücker, to have more accuracy. However, there is no significant improvement reported in comparison with the results from [38] and [39].…”

Section: Pose Estimation From Line Correspondencescontrasting

confidence: 39%

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Analysis of Camera Pose Estimation Using 2D Scene Features for Augmented Reality Applications

Alsadat

Laurendeau

2018

Lecture Notes in Computer Science

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Maîtrise en génie électriqueMaître ès sciences (M. model, the camera has to be localized regarding its surroundings. Camera localization consists of finding the exterior parameters (i.e. its position and orientation) of the camera with respect to the viewed scene and its characteristics.ScIn this thesis, camera pose estimation methods using circle-ellipse and straight line correspondences has been investigated. Circles and lines are two of the geometrical features that are mostly present in structures and buildings. Based on the relationship between the 3D features and their corresponding 2D data detected in the image, the position and orientation of the camera is estimated.

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Section: Pose Estimation From Line Correspondencescontrasting

confidence: 39%

“…The approach proposed in [38] is a non-iterative method called Robust PnL (RPnL). It assumes the line with the longest projection on the image plane to be an intermediate coordinate system between the world and the camera frames, see Figure 4.…”

Section: Pose Estimation From Line Correspondencesmentioning

confidence: 99%

Analysis of Camera Pose Estimation Using 2D Scene Features for Augmented Reality Applications

Alsadat

Laurendeau

2018

Lecture Notes in Computer Science

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“…This method has been recently extended to full pose estimation (rotation+translation) in [33], by combining Pluecker 3D line parameterization with a DLT-like estimation algorithm. [44] combines the former P3L algorithms to compute pose by optimizing a cost function built from line triplets. Finally, [23] shows promising results by formulating the problem in terms of a system of symmetric polynomials.…”

Section: Related Workmentioning

confidence: 99%

“…Regarding state-of-the-art, we compare against the following PnL algorithms: RPnL [44], Mirzaei [28] and Pluecker [33]. As for PnP methods we will include EPnP [24] and OPnP [45]; and the DLT proposed in [17] for the PnPL.Our two approaches will be denoted as EPnPL and OPnPL.…”

Section: Synthetic Experimentsmentioning

confidence: 99%

Accurate and Linear Time Pose Estimation from Points and Lines

Vakhitov

Funke

Moreno-Noguer

2016

Lecture Notes in Computer Science

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Abstract. The Perspective-n-Point (PnP) problem seeks to estimate the pose of a calibrated camera from n 3D-to-2D point correspondences. There are situations, though, where PnP solutions are prone to fail because feature point correspondences cannot be reliably estimated (e.g. scenes with repetitive patterns or with low texture). In such scenarios, one can still exploit alternative geometric entities, such as lines, yielding the so-called Perspective-n-Line (PnL) algorithms. Unfortunately, existing PnL solutions are not as accurate and efficient as their point-based counterparts. In this paper we propose a novel approach to introduce 3D-to-2D line correspondences into a PnP formulation, allowing to simultaneously process points and lines. For this purpose we introduce an algebraic line error that can be formulated as linear constraints on the line endpoints, even when these are not directly observable. These constraints can then be naturally integrated within the linear formulations of two state-of-the-art point-based algorithms, the OPnP [45] and the EPnP [24], allowing them to indistinctly handle points, lines, or a combination of them. Exhaustive experiments show that the proposed formulation brings remarkable boost in performance compared to only point or only line based solutions, with a negligible computational overhead compared to the original OPnP and EPnP.

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“…We use a method which solves the PnL problem with an algorithm like RANSAC explained in [9], and estimate the camera pose RT i cw . This method mainly use RPnL [13] for solving the PnL problem. Suppose we have LC i which is K i sets of 2D-3D line segment correspondences, we randomly select four 2D-3D line segment correspondences from LC i .…”

Section: Solution For the Pnl Problemmentioning

confidence: 99%

3D Line Segment Based Model Generation by RGB-D Camera for Camera Pose Estimation

Nakayama

Saitō

Shimizu

et al. 2015

Computer Vision - ACCV 2014 Workshops

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Abstract. In this paper, we propose a novel method for generating 3D line segment based model from an image sequence taken with a RGB-D camera. Constructing 3D geometrical representation by 3D model is essential for model based camera pose estimation that can be performed by corresponding 2D features in images with 3D features of the captured scene. While point features are mostly used as such features for conventional camera pose estimation, we aim to use line segment features for improving the performance of the camera pose estimation. In this method, using RGB images and depth images of two continuous frames, 2D line segments from the current frame and 3D line segments from the previous frame are corresponded. The 2D-3D line segment correspondences provide camera pose of the current frame. All of 2D line segments are finally back-projected to the world coordinate based on the estimated camera pose for generating 3D line segment based model of the target scene. In experiments, we confirmed that the proposed method can successfully generate line segment based models, while 3D models based on the point features often fail to successfully represent the target scene.

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Robust and Efficient Pose Estimation from Line Correspondences

Cited by 55 publications

References 17 publications

Analysis of Camera Pose Estimation Using 2D Scene Features for Augmented Reality Applications

Analysis of Camera Pose Estimation Using 2D Scene Features for Augmented Reality Applications

Accurate and Linear Time Pose Estimation from Points and Lines

3D Line Segment Based Model Generation by RGB-D Camera for Camera Pose Estimation

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