| 1. |
- Ask, Erik, et al.
(författare)
-
Minimal Structure and Motion Problems for TOA and TDOA Measurements with Collinearity Constraints
- 2013
-
Ingår i: 2nd International Conference on Pattern Recognition Applications and Methods, Proceedings of. - 9789898565419 ; , s. 425-429
-
Konferensbidrag (refereegranskat)abstract
- Structure from sound can be phrased as the problem of determining the position of a number of microphones and a number of sound sources given only the recorded sounds. In this paper we study minimal structure from sound problems in both TOA (time of arrival) and TDOA (time difference of arrival) settings with collinear constraints on e.g. the microphone positions. Three such minimal cases are analyzed and solved with efficient and numerically stable techniques. An experimental validation of the solvers are performed on both simulated and real data. In the paper we also show how such solvers can be utilized in a RANSAC framework to perform robust matching of sound features and then used as initial estimates in a robust non-linear leastsquares optimization.
|
|
| 2. |
- Batstone, Kenneth, et al.
(författare)
-
Collaborative merging of radio SLAM maps in view of crowd-sourced data acquisition and big data
- 2019
-
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
-
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.
|
|
| 3. |
- Flood, Gabrielle, et al.
(författare)
-
Stochastic Analysis of Time-Difference and Doppler Estimates for Audio Signals
- 2019
-
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
-
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.
|
|
| 4. |
- Li, Zhongguo, et al.
(författare)
-
Template based human pose and shape estimation from a single RGB-D image
- 2019
-
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
-
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.
|
|
| 5. |
- Medved, Dennis, et al.
(författare)
-
Improving the Detection of Relations Between Objects in an Image Using Textual Semantics
- 2015
-
Ingår i: Pattern Recognition Applications and Methods /Lecture Notes in Computer Science. - Cham : Springer International Publishing. - 9783319255293 - 9783319255309 ; 9443, s. 133-145
-
Konferensbidrag (refereegranskat)abstract
- In this article, we describe a system that classifies relations between entities extracted from an image. We started from the idea that we could utilize lexical and semantic information from text associated with the image, such as captions or surrounding text, rather than just the geometric and visual characteristics of the entities found in the image. We collected a corpus of images from Wikipedia together with their corresponding articles. In our experimental setup, we extracted two kinds of entities from the images, human beings and horses, and we defined three relations that could exist between them: Ride, Lead,or None. We used geometric features as a baseline to identify the relations between the entities and we describe the improvements brought by the addition of bag-of-word features and predicate–argument structures that we extracted from the text. The best semantic model resulted in a relative error reduction of more than 18 % over the baseline
|
|
| 6. |
- Valtonen Örnhag, Marcus, et al.
(författare)
-
Enforcing the General Planar Motion Model : Bundle Adjustment for Planar Scenes
- 2020
-
Ingår i: Pattern Recognition Applications and Methods - 8th International Conference, ICPRAM 2019, Revised Selected Papers. - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. - 9783030400132 ; 11996 LNCS, s. 119-135
-
Konferensbidrag (refereegranskat)abstract
- In this paper we consider the case of planar motion, where a mobile platform equipped with two cameras moves freely on a planar surface. The cameras are assumed to be directed towards the floor, as well as being connected by a rigid body motion, which constrains the relative motion of the cameras and introduces new geometric constraints. In the existing literature, there are several algorithms available to obtain planar motion compatible homographies. These methods, however, do not minimise a physically meaningful quantity, which may lead to issues when tracking the mobile platform globally. As a remedy, we propose a bundle adjustment algorithm tailored for the specific problem geometry. Due to the new constrained model, general bundle adjustment frameworks, compatible with the standard six degree of freedom model, are not directly applicable, and we propose an efficient method to reduce the computational complexity, by utilising the sparse structure of the problem. We explore the impact of different polynomial solvers on synthetic data, and highlight various trade-offs between speed and accuracy. Furthermore, on real data, the proposed method shows an improvement compared to generic methods not enforcing the general planar motion model.
|
|
| 7. |
- Örnhag, Marcus Valtonen, et al.
(författare)
-
Efficient Radial Distortion Correction for Planar Motion
- 2020
-
Ingår i: Pattern Recognition Applications and Methods - 9th International Conference, ICPRAM 2020, Revised Selected Papers. - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. - 9783030661243 ; 12594 LNCS, s. 46-63
-
Konferensbidrag (refereegranskat)abstract
- In this paper we investigate simultaneous radial distortion calibration and motion estimation for vehicles travelling parallel to planar surfaces. This is done by estimating the inter-image homography between two poses, as well as the distortion parameter. Radial distortion correction is often performed as a pre-calibration step; however, accurately estimating the distortion profile without special scene requirements may make such procedures obsolete. As many modern day consumer cameras are affected by radial distortion to some degree, there is a great potential to reduce production time, if properly implemented. We devise two polynomial solvers, for radially distorted homographies compatible with different models of planar motion. We show that the algorithms are numerically stable, and sufficiently fast to be incorporated in a real-time frameworks. Furthermore, we show on both synthetic and real data, that the proposed solvers perform well compared to competing methods.
|
|
| 8. |
- Örnhag, Marcus Valtonen, et al.
(författare)
-
Fast Non-minimal Solvers for Planar Motion Compatible Homographies
- 2019
-
Ingår i: ICPRAM 2019 - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods. - : SCITEPRESS - Science and Technology Publications. - 9789897583513 ; , s. 40-51
-
Konferensbidrag (refereegranskat)abstract
- This paper presents a novel polynomial constraint for homographies compatible with the general planar motion model. In this setting, compatible homographies have five degrees of freedom-instead of the general case of eight degrees of freedom-and, as a consequence, a minimal solver requires 2.5 point correspondences. The existing minimal solver, however, is computationally expensive, and we propose using non-minimal solvers, which significantly reduces the execution time of obtaining a compatible homography, with accuracy and robustness comparable to that of the minimal solver. The proposed solvers are compared with the minimal solver and the traditional 4-point solver on synthetic and real data, and demonstrate good performance, in terms of speed and accuracy. By decomposing the homographies obtained from the different methods, it is shown that the proposed solvers have future potential to be incorporated in a complete Simultaneous Localization and Mapping (SLAM) framework.
|
|
| 9. |
- Örnhag, Marcus Valtonen, et al.
(författare)
-
Planar motion bundle adjustment
- 2019
-
Ingår i: ICPRAM 2019 - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods. - : SCITEPRESS - Science and Technology Publications. - 9789897583513 ; , s. 24-31
-
Konferensbidrag (refereegranskat)abstract
- In this paper we consider trajectory recovery for two cameras directed towards the floor, and which are mounted rigidly on a mobile platform. Previous work for this specific problem geometry has focused on locally minimising an algebraic error between inter-image homographies to estimate the relative pose. In order to accurately track the platform globally it is necessary to refine the estimation of the camera poses and 3D locations of the feature points, which is commonly done by utilising bundle adjustment; however, existing software packages providing such methods do not take the specific problem geometry into account, and the result is a physically inconsistent solution. We develop a bundle adjustment algorithm which incorporates the planar motion constraint, and devise a scheme that utilises the sparse structure of the problem. Experiments are carried out on real data and the proposed algorithm shows an improvement compared to established generic methods.
|
|
| 10. |
- Örnhag, Marcus Valtonen, et al.
(författare)
-
Radially distorted planar motion compatible homographies
- 2020
-
Ingår i: Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods : ICPRAM 2020 - ICPRAM 2020. - : SCITEPRESS - Science and Technology Publications. - 9789897583971 ; 1, s. 280-288
-
Konferensbidrag (refereegranskat)abstract
- Fast and accurate homography estimation is essential to many computer vision applications, including scene degenerate cases and planarity detection. Such cases arise naturally in man-made environments, and failure to handle them will result in poor positioning estimates. Most modern day consumer cameras are affected by some level of radial distortion, which must be compensated for in order to get accurate estimates. This often demands calibration procedures, with specific scene requirements, and off-line processing. In this paper a novel polynomial solver for radially distorted planar motion compatible homographies is presented. The proposed algorithm is fast and numerically stable, and is proven on both synthetic and real data to work well inside a RANSAC loop.
|
|
