Tracking extended objects using extrusion Random Hypersurface Models

Zea, Antonio; Faion, Florian; Hanebeck, Uwe D.

doi:10.1109/sdf.2014.6954722

Cited by 10 publications

(15 citation statements)

References 9 publications

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“…74-79], it was shown that a robust height estimate can only be achieved if the likelihood is reformulated to combine two different association approaches in a single model. When reformulating a random hypersurface model (RHM) [4], [13] for 3D EOT to an extrusion RHM [18], [19], [30], a GAM is applied for the angular and a spatial distribution model for the height association. This combination proved to be the most suitable compared to a GAM.…”

Section: Discussionmentioning

confidence: 99%

Harmonic Functions for Three-Dimensional Shape Estimation in Cylindrical Coordinates

Baur

Reuter

Zea

et al. 2022

2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

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With the high resolution of modern sensors such as multilayer LiDARs, estimating the 3D shape in an extended object tracking procedure is possible. In recent years, 3D shapes have been estimated in spherical coordinates using Gaussian processes, spherical double Fourier series or spherical harmonics. However, observations have shown that in many scenarios only a few measurements are obtained from top or bottom surfaces, leading to error-prone estimates in spherical coordinates. Therefore, in this paper we propose to estimate the shape in cylindrical coordinates instead, applying harmonic functions. Specifically, we derive an expansion for 3D shapes in cylindrical coordinates by solving a boundary value problem for the Laplace equation. This shape representation is then integrated in a plain greedy association model and compared to shape estimation procedures in spherical coordinates. Since the shape representation is only integrated in a basic estimator, the results are preliminary and a detailed discussion for future work is presented at the end of the paper.

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Section: Discussionmentioning

confidence: 99%

Harmonic Functions for Three-Dimensional Shape Estimation in Cylindrical Coordinates

Baur

Reuter

Zea

et al. 2022

2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

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“…φk,l = atan2(y ẑ, x ẑ) (18) with x ẑ and y ẑ as x and y coordinate of ẑk,l , respectively. Using (15), our shape estimation algorithm is implemented with an unscented Kalman filter [27] in this paper.…”

Section: Measurement Modelmentioning

confidence: 99%

“…If 3D contour measurements gathered by devices such as multilayer LiDAR sensors or depth cameras are available, shape estimation algorithms using Gaussian processes [12], [13], [14] or spherical harmonics [15] for star-convex shape representation can be applied. In addition, 3D EOT measurement models using basic geometric shapes [16], [17] or restricted shape estimation [18] have been proposed if prior knowledge is available, detailed shape information is not required in the application or computational complexity is to be reduced.…”

Section: Introductionmentioning

confidence: 99%

Shape Estimation and Tracking using Spherical Double Fourier Series for Three-Dimensional Range Sensors

Baur

Reuter

Zea

et al. 2021

2021 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

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In this paper, a novel measurement model based on spherical double Fourier series (DFS) for estimating the 3D shape of a target concurrently with its kinematic state is introduced. Here, the shape is represented as a star-convex radial function, decomposed as spherical DFS. In comparison to ordinary DFS, spherical DFS do not suffer from ambiguities at the poles. Details will be given in the paper. The shape representation is integrated into a Bayesian state estimator framework via a measurement equation. As range sensors only generate measurements from the target side facing the sensor, the shape representation is modified to enable application of shape symmetries during the estimation process. The model is analyzed in simulations and compared to a shape estimation procedure using spherical harmonics. Finally, shape estimation using spherical and ordinary DFS is compared to analyze the effect of the pole problem in extended object tracking (EOT) scenarios.

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“…However, more complex models are usually necessary for accurate cable modeling and tracking, like a B-spline model with multiple chained random matrices, proposed in [6]. A similar approach, but using Bezier curves and rectangle chains, was proposed in [12], while in [13] NURBS curves were used.…”

Section: A Dlo Representationmentioning

confidence: 99%

Measuring Bending Angle and Hallucinating Shape of Elongated Deformable Objects

Kicki

Bednarek

Walas

2018

2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)

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While the manipulation of rigid objects is an extensively explored research topic, deformable linear object (DLO) manipulation seems significantly underdeveloped. A potential reason for this is the inherent difficulty in describing and observing the state of the DLO as its geometry changes during manipulation. This paper proposes an algorithm for fast-tracking the shape of a DLO based on the masked image. Having no prior knowledge about the tracked object, the proposed method finds a reliable representation of the shape of the tracked object within tens of milliseconds. This algorithm's main idea is to first skeletonize the DLO mask image, walk through the parts of the DLO skeleton, arrange the segments into an ordered path, and finally fit a B-spline into it. Experiments show that our solution outperforms the State-of-the-Art approaches in DLO's shape reconstruction accuracy and algorithm running time and can handle challenging scenarios such as severe occlusions, self-intersections, and multiple DLOs in a single image.

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Tracking extended objects using extrusion Random Hypersurface Models

Cited by 10 publications

References 9 publications

Harmonic Functions for Three-Dimensional Shape Estimation in Cylindrical Coordinates

Harmonic Functions for Three-Dimensional Shape Estimation in Cylindrical Coordinates

Shape Estimation and Tracking using Spherical Double Fourier Series for Three-Dimensional Range Sensors

Measuring Bending Angle and Hallucinating Shape of Elongated Deformable Objects

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