Set Distance Functions for 3D Object Recognition

Alexandre, Luı́s A.

doi:10.1007/978-3-642-41822-8_8

Cited by 8 publications

(3 citation statements)

References 8 publications

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“…The Hausdorff distance or Hausdorff metric is used in a wide range of fields, such as point cloud [32] and meshes [33] comparison, object recognition [34], and image comparison and matching [35]. This metric proves to be a robust strategy for the similarity evaluation of two compact and non-empty sub-sets within a metric space.…”

Section: Global and Local Hausdorff Metrics As Geometric Accuracy Indmentioning

confidence: 99%

Photogrammetric, Geometrical, and Numerical Strategies to Evaluate Initial and Current Conditions in Historical Constructions: A Test Case in the Church of San Lorenzo (Zamora, Spain)

et al. 2016

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Identifying and quantifying the potential causes of damages to a construction and evaluating its current stability have become an imperative task in today's world. However, the existence of variables, unknown conditions and a complex geometry hinder such work, by hampering the numerical results that simulate its behavior. Of the mentioned variables, the following can be highlighted: (i) the lack of historical information; (ii) the mechanical properties of the material; (iii) the initial geometry and (iv) the interaction with other structures. Within the field of remote sensors, the laser scanner and photogrammetric systems have become especially valuable for construction analysis. Such sensors are capable of providing highly accurate and dense geometrical data with which to assess a building's condition. It is also remarkable, that the latter provide valuable radiometric data with which to identify the properties of the materials, and also evaluate and monitor crack patterns. Motivated by this, the present article investigates the potential offered by the combined use of photogrammetric techniques (DIC and SfM), as well as geometrical (NURBs and Hausdorff distance) and numerical strategies (FEM) to assess the origin of the damage (through an estimation of the initial conditions) and give an evaluation of the current stability (considering the deformation and the damage).

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Section: Global and Local Hausdorff Metrics As Geometric Accuracy Indmentioning

confidence: 99%

Photogrammetric, Geometrical, and Numerical Strategies to Evaluate Initial and Current Conditions in Historical Constructions: A Test Case in the Church of San Lorenzo (Zamora, Spain)

et al. 2016

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“…This issue is mentioned even by the authors of the most recent segmentation-based object recognition systems, such as [15]. As an alternative, in recent years multiple techniques of neighborhood-based, local 3D surface description have been developed, such as PFH [23], FPFH [21], PFHRGB [4], CVFH [2]. The applications for such descriptors range from point cloud registration to object part recognition, fast orientation retrieval and, as descriptors become more accurate, raise the possibility of segmentation-less object detection.…”

Section: Introduction and Related Workmentioning

confidence: 99%

“…PFH, FPFH, PFHRGB [23,21,4]. The former are multi-dimensional histograms of parameters describing the relations of point pairs position and normal vectors, whereas FPFH is an approximate speed-up version of PFH and PFHRGB is PFH with three added histograms representing the RGB color relations between these point pairs.…”

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confidence: 99%

Keypoint-Less, Heuristic Application of Local 3D Descriptors

Harasymowicz-Boggio

Chechliński

2017

Foundations of Computing and Decision Sciences

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Abstract. One of the most important topics in the research concerning 3D local descriptors is computational efficiency. The state-of-the-art approach addressing this matter consists in using keypoint detectors that effectively limit the number of points for which the descriptors are computed. However, the choice of keypoints is not trivial and might have negative implications, such as the omission of relevant areas. Instead, focusing on the task of single object detection, we propose a keypoint-less approach to attention focusing in which the full scene is processed in a hierarchical manner: weaker, less rejective and faster classification methods are used as heuristics for increasingly robust descriptors, which allows to use more demanding algorithms at the top level of the hierarchy. We have developed a massively-parallel, open source object recognition framework, which we use to explore the proposed method on demanding, realistic indoor scenes, applying the full power available in modern computers.

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A Biological Motivated Multi-scale Keypoint Detector for local 3D Descriptors

Filipe

Alexandre

2014

Advances in Visual Computing

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Set Distance Functions for 3D Object Recognition

Cited by 8 publications

References 8 publications

Photogrammetric, Geometrical, and Numerical Strategies to Evaluate Initial and Current Conditions in Historical Constructions: A Test Case in the Church of San Lorenzo (Zamora, Spain)

Photogrammetric, Geometrical, and Numerical Strategies to Evaluate Initial and Current Conditions in Historical Constructions: A Test Case in the Church of San Lorenzo (Zamora, Spain)

Keypoint-Less, Heuristic Application of Local 3D Descriptors

A Biological Motivated Multi-scale Keypoint Detector for local 3D Descriptors

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