Improving the Agility of Keyframe-Based SLAM

Klein, Georg; Murray, David

doi:10.1007/978-3-540-88688-4_59

Cited by 265 publications

(229 citation statements)

References 17 publications

(42 reference statements)

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“…References to recent work can be found in [7,17]. These methods can track the 6DOF motion of a camera from point and line features in a video sequence of a rigid scene.…”

Section: Camera Pose Estimationmentioning

confidence: 99%

Video-based, real-time multi-view stereo

Vogiatzis

Hernández

2011

Image and Vision Computing

135

125

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We investigate the problem of obtaining a dense reconstruction in real-time, from a live video stream. In recent years, Multi-view stereo (MVS) has received considerable attention and a number of methods have been proposed. However, most methods operate under the assumption of a relatively sparse set of still images as input and unlimited computation time. Video based MVS has received less attention despite the fact that video sequences offer significant benefits in terms of usability of MVS systems. In this paper we propose a novel video based MVS algorithm that is suitable for real-time, interactive 3d modeling with a hand-held camera. The key idea is a per-pixel, probabilistic depth estimation scheme that updates posterior depth distributions with every new frame. The current implementation is capable of updating 15 million distributions per second. We evaluate the proposed method against the state-of-the-art real-time MVS method and show improvement in terms of accuracy. AbstractWe investigate the problem of obtaining a dense reconstruction in real-time, from a live video stream. In recent years, Multi-view stereo (MVS) has received considerable attention and a number of methods have been proposed. However, most methods operate under the assumption of a relatively sparse set of still images as input and unlimited computation time. Video based MVS has received less attention despite the fact that video sequences offer significant benefits in terms of usability of MVS systems. In this paper we propose a novel video based MVS algorithm that is suitable for real-time, interactive 3d modeling with a hand-held camera. The key idea is a per-pixel, probabilistic depth estimation scheme that updates posterior depth distributions with every new frame. The current implementation is capable of updating 15 million distributions per second. We evaluate the proposed method against the state-of-the-art real-time MVS method and show improvement in terms of accuracy.

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“…References to recent work can be found in [7,17]. These methods can track the 6DOF motion of a camera from point and line features in a video sequence of a rigid scene.…”

Section: Camera Pose Estimationmentioning

confidence: 99%

Video-based, real-time multi-view stereo

Vogiatzis

Hernández

2011

Image and Vision Computing

135

125

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“…In particular, when using keypoints, information contained in straight or curved edges -which especially in man-made environments make up a large part of the image -is discarded. Several approaches have been made in the past to remedy this by including edge-based [16,6] or even region-based [5] features. Yet, since the estimation of the high-dimensional feature space is tedious, they are rarely used in practice.…”

Section: Related Workmentioning

confidence: 99%

LSD-SLAM: Large-Scale Direct Monocular SLAM

Engel¹,

Schöps²,

Cremers³

2014

Lecture Notes in Computer Science

2,762

1,974

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Abstract. We propose a direct (feature-less) monocular SLAM algorithm which, in contrast to current state-of-the-art regarding direct methods, allows to build large-scale, consistent maps of the environment. Along with highly accurate pose estimation based on direct image alignment, the 3D environment is reconstructed in real-time as pose-graph of keyframes with associated semi-dense depth maps. These are obtained by filtering over a large number of pixelwise small-baseline stereo comparisons. The explicitly scale-drift aware formulation allows the approach to operate on challenging sequences including large variations in scene scale. Major enablers are two key novelties: (1) a novel direct tracking method which operates on sim(3), thereby explicitly detecting scale-drift, and (2) an elegant probabilistic solution to include the effect of noisy depth values into tracking. The resulting direct monocular SLAM system runs in real-time on a CPU.

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“…It improves the problem that the FAST detector does not have directionality, and uses the fast binary descriptor BRIEF to accelerate the feature extraction of the whole image At present, there are many visual odometry and visual SLAM based on line segment features too. Georg Klein [3] Used point and line segment features to constrcut a SLAM system based on key reconnaissance optimization, Guoxuan Zhang [4] proposed the pure line features of SLSLAM(Stereo Line-based SLAM), framework based on the binocular vision SLAM system, including the construction of line feature map of the scene, closed loop detection and so on. According to using infrared image for VSLAM and comprehensive efficiency and cost, this paper proposed an algorithm which firstly doing image enhancement and denoising and then deal with point and line feature extraction.…”

Section: Introductionmentioning

confidence: 99%

Line Features of Detail Enhancement Thermal Infrared Image for SLAM

Zhang

et al. 2017

MATEC Web Conf.

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Abstract.To solve the problem of simultaneous localization and mapping of mobile robot vision navigation using infrared thermal imaging, A point-line feature extraction and matching algorithm after infrared image enhancement is proposed for visual odometry. We first used a guided filter to smooth the input image and separate it into the base layer and the detail layer. Then constraining the gradient of the detail will be used gain mask to enhance it. Finally, the two parts of the image combined with weighted coefficients will be exported into the second guided filter. The output image will use LSD to extract line feature, then using ORB algorithm will get point feature extraction and matching from line feature image . The results show the it can effectively improve the defect of infrared image blurred with similar background temperature and difficult to extract image features for mobile robot visual SLAM.

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Improving the Agility of Keyframe-Based SLAM

Cited by 265 publications

References 17 publications

Video-based, real-time multi-view stereo

Video-based, real-time multi-view stereo

LSD-SLAM: Large-Scale Direct Monocular SLAM

Line Features of Detail Enhancement Thermal Infrared Image for SLAM

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