Adapting a real-time monocular visual SLAM from conventional to omnidirectional cameras

Gutiérrez, Daniel; Rituerto, Alejandro; Montiel, José María; Guerrero, J. J.

doi:10.1109/iccvw.2011.6130262

Cited by 32 publications

(29 citation statements)

References 24 publications

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“…The proposed localization system builds on a recently proposed real time omnidirectional SLAM method [8]. In this paper we validate its suitability for indoor environments, where catadioptric vision systems suffer bigger distortions, and enhance it with topologicalsemantic information required for human guidance.…”

Section: Introductionmentioning

confidence: 81%

Wearable omnidirectional vision system for personal localization and guidance

Murillo

Gutiérrez-Gómez

Rituerto

et al. 2012

2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

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Autonomous navigation and recognition of the environment are fundamental abilities for people extensively studied in computer vision and robotics fields. Expansion of low cost wearable sensing provides interesting opportunities for assistance systems that augment people navigation and recognition capabilities. This work presents our wearable omnidirectional vision system and a novel twophase localization approach running on it. It runs stateof-the-art real time visual odometry adapted to catadioptric images augmented with topological-semantic information. The presented approach benefits from using wearable sensors to improve visual odometry results with true scaled solution. The wide field of view of catadioptric vision system used makes features last longer in the field of view and allows more compact location representation which facilitates topological place recognition. Experiments in this paper show promising ego-localization results in realistic settings, providing good true scaled visual odometry estimation and recognition of indoor regions.

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Section: Introductionmentioning

confidence: 81%

Wearable omnidirectional vision system for personal localization and guidance

Murillo

Gutiérrez-Gómez

Rituerto

et al. 2012

2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

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“…In this work we perform SLAM with an omnidirectional camera on a helmet carried by a human operator [9]. Since the head moves vertically with the step frequency during walking, SLAM visual odometry can be used to estimate the step frequency by spectral analysis.…”

Section: Camera Statementioning

confidence: 99%

“…The initial unescaled trajectory and map corresponding to each image sequence are constructed with the SLAM approach presented in [9].…”

Section: Scaling Of the Trajectorymentioning

confidence: 99%

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Full scaled 3D visual odometry from a single wearable omnidirectional camera

Gutiérrez-Gómez

Puig

Guerrero

2012

2012 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-In the last years monocular SLAM has been widely used to obtain highly accurate maps and trajectory estimations of a moving camera. However, one of the issues of this approach is that, due to the impossibility of the depth being measured in a single image, global scale is not observable and scene and camera motion can only be recovered up to scale. This problem gets aggravated as we deal with larger scenes since it is more likely that scale drift arises between different map portions and their corresponding motion estimates. To compute the absolute scale we need to know some kind of dimension of the scene (e.g., actual size of an element of the scene, velocity of the camera or baseline between two frames) and somehow integrate it in the SLAM estimation. In this paper, we present a method to recover the scale of the scene using an omnidirectional camera mounted on a helmet. The high precision of visual SLAM allows the head vertical oscillation during walking to be perceived in the trajectory estimation. By performing a spectral analysis on the camera vertical displacement, we can measure the step frequency. We relate the step frequency to the speed of the camera by an empirical formula based on biomedical experiments on human walking. This speed measurement is integrated in a particle filter to estimate the current scale factor and the 3D motion estimation with its true scale. We evaluated our approach using image sequences acquired while a person walks. Our experiments show that the proposed approach is able to cope with scale drift.

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“…Its sensor models and applications have been studied for years. The spherical perspective [11], global description of omni-directional images [12], and rotation and scale invariance of image patches [13] of a spherical camera have been studied theoretically. However, no physical spherical camera has been produced due to the challenging manufacturing process.…”

Section: Introductionmentioning

confidence: 99%

Template Matching for Wide-Baseline Panoramic Images from a Vehicle-Borne Multi-Camera Rig

Hong³

et al. 2018

IJGI

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Automatic detection and locating of objects such as poles, traffic signs, and building corners in street scenes captured from a mobile mapping system has many applications. Template matching is a technique that could automatically recognise the counterparts or correspondents of an object from multi-view images. In this study, we aim at finding correspondents of an object from wide baseline panoramic images with large geometric deformations from sphere projection and significant systematic errors from multi-camera rig geometry. Firstly, we deduce the camera model and epipolar model of a multi-camera rig system. Then, epipolar errors are analysed to determine the search area for pixelwise matching. A low-cost laser scanner is optionally used to constrain the depth of an object. Lastly, several classic feature descriptors are introduced to template matching and evaluated on the multi-view panoramic image dataset. We propose a template matching method combining a fast variation of a scale-invariant feature transform (SIFT) descriptor. Our method experimentally achieved the best performance in terms of accuracy and efficiency comparing to other feature descriptors and the most recent robust template matching methods.

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Adapting a real-time monocular visual SLAM from conventional to omnidirectional cameras

Cited by 32 publications

References 24 publications

Wearable omnidirectional vision system for personal localization and guidance

Wearable omnidirectional vision system for personal localization and guidance

Full scaled 3D visual odometry from a single wearable omnidirectional camera

Template Matching for Wide-Baseline Panoramic Images from a Vehicle-Borne Multi-Camera Rig

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