| 1. |
- Arcelli, Carlo, et al.
(författare)
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Computing and analysing convex deficiencies to characterise 3D complex objects
- 2005
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Ingår i: Image and Vision Computing: Discrete Geometry for Computer Imagery. ; 23:2, s. 203-211
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Tidskriftsartikel (refereegranskat)abstract
- Entities such as object components, cavities, tunnels and concavities in 3D digital images can be useful in the framework of object analysis. For each object component, we first identify its convex deficiencies, by subtracting the object component from a covering polyhedron approximating the convex hull. Watershed segmentation is then used to decompose complex convex deficiencies into simpler parts, corresponding to individual cavities, concavities and tunnels of the object component. These entities are finally described by means of a representation system accounting for the shape features characterising them.
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| 2. |
- Batstone, Kenneth, et al.
(författare)
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Collaborative merging of radio SLAM maps in view of crowd-sourced data acquisition and big data
- 2019
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Ingår i: ICPRAM 2019 - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods. - : SCITEPRESS - Science and Technology Publications. - 9789897583513 ; , s. 807-813
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Konferensbidrag (refereegranskat)abstract
- Indoor localization and navigation is a much researched and difficult problem. The best solutions, usually use expensive specialized equipment and/or prior calibration of some form. To the average person with smart or Internet-Of-Things devices, these solutions are not feasible, particularly in large scales. With hardware advancements making Ultra-Wideband devices more accurate and low powered, this unlocks the potential of having such devices in commonplace around factories and homes, enabling an alternative method of navigation. Therefore, indoor anchor calibration becomes a key problem in order to implement these devices efficiently and effectively. In this paper, we present a method to fuse radio SLAM (also known as Time-Of-Arrival self-calibration) maps together in a linear way. In doing so we are then able to collaboratively calibrate the anchor positions in 3D to native precision of the devices. Furthermore, we introduce an automatic scheme to determine which of the maps are best to use to further improve the anchor calibration and its robustness but also show which maps could be discarded. Additionally, when a map is fused in a linear way, it is a very computationally cheap process and produces a reasonable map which is required to push for crowd-sourced data acquisition.
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| 3. |
- Borgefors, Gunilla, et al.
(författare)
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Computing skeletons in three dimensions
- 1999
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Ingår i: Pattern Recognition. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0031-3203 .- 1873-5142. ; 32:7, s. 1225-1236
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Tidskriftsartikel (refereegranskat)abstract
- Skeletonization will probably become as valuable a tool for shape analysis in 3D, as it is in 2D. We present a topology preserving 3D skeletonization method which computes both surface and curve skeletons whose voxels are labelled with the D-6 distance to
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| 4. |
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| 5. |
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| 6. |
- Borgefors, Gunilla, et al.
(författare)
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Discrete Skeletons from Distance Transforms in 2D and 3D
- 2008
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Ingår i: Medial Representations. - Netherlands : Springer Verlag. ; , s. 155-190
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- We present discrete methods to compute the digital skeleton of shapes in 2D and 3D images. In 2D, the skeleton is a set of curves, while in 3D it will be a set of surfaces and curves, the surface skeleton, or a set of curves, the curve skeleton. A general scheme could, in principle, be followed for both 2D and 3D discrete skeletonization. However, we will describe one approach for 2D skeletonization, mainly based on marking in the distance transform the shape elements that should be assigned to the skeleton, and another approach for 3D skeletonization, mainly based on iterated element removal. In both cases, the distance transform of the image will play a key role to obtain skeletons reflecting important shape features such as symmetry, elongation, and width.
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| 7. |
- Borgefors, Gunilla, et al.
(författare)
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Skeletonizing Volume Objects. Part II : From Surface to Curve Skeleton
- 1998
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Ingår i: Advances in Pattern Recognition Joint IAPR International Workshops SSPR'98 and SPR'98 Sydney, Australia, August 11–13, 1998 Proceedings. - : Springer Verlag. - 9783540648581 ; , s. 220-229
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Konferensbidrag (refereegranskat)abstract
- Volume imaging techniques are becoming common and skeletonization has begun to prove valuable for shape analysis also in 3D. In this paper, a method to reduce solid volume objects to their 3D curve skeletons is presented. The method consists of two major steps.
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| 8. |
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| 9. |
- Flood, Gabrielle, et al.
(författare)
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Stochastic Analysis of Time-Difference and Doppler Estimates for Audio Signals
- 2019
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Ingår i: Pattern Recognition Applications and Methods - 7th International Conference, ICPRAM 2018, Revised Selected Papers. - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. - 9783030054984 ; 11351 LNCS, s. 116-138
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Konferensbidrag (refereegranskat)abstract
- Pairwise comparison of sound and radio signals can be used to estimate the distance between two units that send and receive signals. In a similar way it is possible to estimate differences of distances by correlating two received signals. There are essentially two groups of such methods, namely methods that are robust to noise and reverberation, but give limited precision and sub-sample refinements that are more sensitive to noise, but also give higher precision when they are initialized close to the real translation. In this paper, we present stochastic models that can explain the precision limits of such sub-sample time-difference estimates. Using these models new methods are provided for precise estimates of time-differences as well as Doppler effects. The developed methods are evaluated and verified on both synthetic and real data.
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| 10. |
- Li, Zhongguo, et al.
(författare)
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Template based human pose and shape estimation from a single RGB-D image
- 2019
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Ingår i: ICPRAM 2019 - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods. - : SCITEPRESS - Science and Technology Publications. - 9789897583513 ; , s. 574-581
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Konferensbidrag (refereegranskat)abstract
- Estimating the 3D model of the human body is needed for many applications. However, this is a challenging problem since the human body inherently has a high complexity due to self-occlusions and articulation. We present a method to reconstruct the 3D human body model from a single RGB-D image. 2D joint points are firstly predicted by a CNN-based model called convolutional pose machine, and the 3D joint points are calculated using the depth image. Then, we propose to utilize both 2D and 3D joint points, which provide more information, to fit a parametric body model (SMPL). This is implemented through minimizing an objective function, which measures the difference of the joint points between the observed model and the parametric model. The pose and shape parameters of the body are obtained through optimization and the final 3D model is estimated. The experiments on synthetic data and real data demonstrate that our method can estimate the 3D human body model correctly.
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