scholarly journals Camera Calibration Using Catenary

Author(s):  
Okay Arık ◽  
Seniha Esen Yuksel

In this work, we introduce a novel calibration technique based on a hanging chain curve replacing the checkerboard-based methods. It is a known physical phenomenon that a hanging chain or a flexible rope under gravity can be modeled by a special curve called catenary. Therefore, instead of the commonly-used planar calibrator, we propose using multiple shots of a catenary-shaped chain for calibration. This approach can solve the out-of-focus problem which is faced in checkerboard calibration methods when the size of the board is not large enough. Although enlarging a planar calibrator increases the manufacturing time and cost, a simple label chain can create large planar areas as precise as a rigid checkerboard, is easily foldable and transportable. We compare the results of our proposed approach against the widely used checkerboardbased calibration as well as the state-of-the-art calibration methods and show that catenary-based calibration is much more accurate than checkerboard-based calibration by a very large margin and is also very competitive among the other approaches.<br>

2021 ◽  
Author(s):  
Okay Arık ◽  
Seniha Esen Yuksel

In this work, we introduce a novel calibration technique based on a hanging chain curve replacing the checkerboard-based methods. It is a known physical phenomenon that a hanging chain or a flexible rope under gravity can be modeled by a special curve called catenary. Therefore, instead of the commonly-used planar calibrator, we propose using multiple shots of a catenary-shaped chain for calibration. This approach can solve the out-of-focus problem which is faced in checkerboard calibration methods when the size of the board is not large enough. Although enlarging a planar calibrator increases the manufacturing time and cost, a simple label chain can create large planar areas as precise as a rigid checkerboard, is easily foldable and transportable. We compare the results of our proposed approach against the widely used checkerboardbased calibration as well as the state-of-the-art calibration methods and show that catenary-based calibration is much more accurate than checkerboard-based calibration by a very large margin and is also very competitive among the other approaches.<br>


2019 ◽  
Author(s):  
Wengong Jin ◽  
Regina Barzilay ◽  
Tommi S Jaakkola

The problem of accelerating drug discovery relies heavily on automatic tools to optimize precursor molecules to afford them with better biochemical properties. Our work in this paper substantially extends prior state-of-the-art on graph-to-graph translation methods for molecular optimization. In particular, we realize coherent multi-resolution representations by interweaving trees over substructures with the atom-level encoding of the original molecular graph. Moreover, our graph decoder is fully autoregressive, and interleaves each step of adding a new substructure with the process of resolving its connectivity to the emerging molecule. We evaluate our model on multiple molecular optimization tasks and show that our model outperforms previous state-of-the-art baselines by a large margin.


1999 ◽  
Vol 18 (3-4) ◽  
pp. 265-273
Author(s):  
Giovanni B. Garibotto

The paper is intended to provide an overview of advanced robotic technologies within the context of Postal Automation services. The main functional requirements of the application are briefly referred, as well as the state of the art and new emerging solutions. Image Processing and Pattern Recognition have always played a fundamental role in Address Interpretation and Mail sorting and the new challenging objective is now off-line handwritten cursive recognition, in order to be able to handle all kind of addresses in a uniform way. On the other hand, advanced electromechanical and robotic solutions are extremely important to solve the problems of mail storage, transportation and distribution, as well as for material handling and logistics. Finally a short description of new services of Postal Automation is referred, by considering new emerging services of hybrid mail and paper to electronic conversion.


Author(s):  
Alexander Diederich ◽  
Christophe Bastien ◽  
Karthikeyan Ekambaram ◽  
Alexis Wilson

The introduction of automated L5 driving technologies will revolutionise the design of vehicle interiors and seating configurations, improving occupant comfort and experience. It is foreseen that pre-crash emergency braking and swerving manoeuvres will affect occupant posture, which could lead to an interaction with a deploying airbag. This research addresses the urgent safety need of defining the occupant’s kinematics envelope during that pre-crash phase, considering rotated seat arrangements and different seatbelt configurations. The research used two different sets of volunteer tests experiencing L5 vehicle manoeuvres, based in the first instance on 22 50th percentile fit males wearing a lap-belt (OM4IS), while the other dataset is based on 87 volunteers with a BMI range of 19 to 67 kg/m2 wearing a 3-point belt (UMTRI). Unique biomechanics kinematics corridors were then defined, as a function of belt configuration and vehicle manoeuvre, to calibrate an Active Human Model (AHM) using a multi-objective optimisation coupled with a Correlation and Analysis (CORA) rating. The research improved the AHM omnidirectional kinematics response over current state of the art in a generic lap-belted environment. The AHM was then tested in a rotated seating arrangement under extreme braking, highlighting that maximum lateral and frontal motions are comparable, independent of the belt system, while the asymmetry of the 3-point belt increased the occupant’s motion towards the seatbelt buckle. It was observed that the frontal occupant kinematics decrease by 200 mm compared to a lap-belted configuration. This improved omnidirectional AHM is the first step towards designing safer future L5 vehicle interiors.


2021 ◽  
Vol 18 (4) ◽  
pp. 1-22
Author(s):  
Jerzy Proficz

Two novel algorithms for the all-gather operation resilient to imbalanced process arrival patterns (PATs) are presented. The first one, Background Disseminated Ring (BDR), is based on the regular parallel ring algorithm often supplied in MPI implementations and exploits an auxiliary background thread for early data exchange from faster processes to accelerate the performed all-gather operation. The other algorithm, Background Sorted Linear synchronized tree with Broadcast (BSLB), is built upon the already existing PAP-aware gather algorithm, that is, Background Sorted Linear Synchronized tree (BSLS), followed by a regular broadcast distributing gathered data to all participating processes. The background of the imbalanced PAP subject is described, along with the PAP monitoring and evaluation topics. An experimental evaluation of the algorithms based on a proposed mini-benchmark is presented. The mini-benchmark was performed over 2,000 times in a typical HPC cluster architecture with homogeneous compute nodes. The obtained results are analyzed according to different PATs, data sizes, and process numbers, showing that the proposed optimization works well for various configurations, is scalable, and can significantly reduce the all-gather elapsed times, in our case, up to factor 1.9 or 47% in comparison with the best state-of-the-art solution.


Robotics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Victor Massagué Respall ◽  
Stefano Nolfi

We investigate whether standard evolutionary robotics methods can be extended to support the evolution of multiple behaviors by forcing the retention of variations that are adaptive with respect to all required behaviors. This is realized by selecting the individuals located in the first Pareto fronts of the multidimensional fitness space in the case of a standard evolutionary algorithms and by computing and using multiple gradients of the expected fitness in the case of a modern evolutionary strategies that move the population in the direction of the gradient of the fitness. The results collected on two extended versions of state-of-the-art benchmarking problems indicate that the latter method permits to evolve robots capable of producing the required multiple behaviors in the majority of the replications and produces significantly better results than all the other methods considered.


2021 ◽  
Vol 15 (5) ◽  
pp. 1-32
Author(s):  
Quang-huy Duong ◽  
Heri Ramampiaro ◽  
Kjetil Nørvåg ◽  
Thu-lan Dam

Dense subregion (subgraph & subtensor) detection is a well-studied area, with a wide range of applications, and numerous efficient approaches and algorithms have been proposed. Approximation approaches are commonly used for detecting dense subregions due to the complexity of the exact methods. Existing algorithms are generally efficient for dense subtensor and subgraph detection, and can perform well in many applications. However, most of the existing works utilize the state-or-the-art greedy 2-approximation algorithm to capably provide solutions with a loose theoretical density guarantee. The main drawback of most of these algorithms is that they can estimate only one subtensor, or subgraph, at a time, with a low guarantee on its density. While some methods can, on the other hand, estimate multiple subtensors, they can give a guarantee on the density with respect to the input tensor for the first estimated subsensor only. We address these drawbacks by providing both theoretical and practical solution for estimating multiple dense subtensors in tensor data and giving a higher lower bound of the density. In particular, we guarantee and prove a higher bound of the lower-bound density of the estimated subgraph and subtensors. We also propose a novel approach to show that there are multiple dense subtensors with a guarantee on its density that is greater than the lower bound used in the state-of-the-art algorithms. We evaluate our approach with extensive experiments on several real-world datasets, which demonstrates its efficiency and feasibility.


Author(s):  
Yunfei Fu ◽  
Hongchuan Yu ◽  
Chih-Kuo Yeh ◽  
Tong-Yee Lee ◽  
Jian J. Zhang

Brushstrokes are viewed as the artist’s “handwriting” in a painting. In many applications such as style learning and transfer, mimicking painting, and painting authentication, it is highly desired to quantitatively and accurately identify brushstroke characteristics from old masters’ pieces using computer programs. However, due to the nature of hundreds or thousands of intermingling brushstrokes in the painting, it still remains challenging. This article proposes an efficient algorithm for brush Stroke extraction based on a Deep neural network, i.e., DStroke. Compared to the state-of-the-art research, the main merit of the proposed DStroke is to automatically and rapidly extract brushstrokes from a painting without manual annotation, while accurately approximating the real brushstrokes with high reliability. Herein, recovering the faithful soft transitions between brushstrokes is often ignored by the other methods. In fact, the details of brushstrokes in a master piece of painting (e.g., shapes, colors, texture, overlaps) are highly desired by artists since they hold promise to enhance and extend the artists’ powers, just like microscopes extend biologists’ powers. To demonstrate the high efficiency of the proposed DStroke, we perform it on a set of real scans of paintings and a set of synthetic paintings, respectively. Experiments show that the proposed DStroke is noticeably faster and more accurate at identifying and extracting brushstrokes, outperforming the other methods.


Medicina ◽  
2021 ◽  
Vol 57 (4) ◽  
pp. 379
Author(s):  
Bogdan Doroftei ◽  
Ovidiu-Dumitru Ilie ◽  
Ana-Maria Dabuleanu ◽  
Roxana Diaconu ◽  
Radu Maftei ◽  
...  

Background and objectives: The latest reports suggest that follitropin delta is a highly efficient recombinant human follicle-stimulating hormone (r-hFSH) that became a part of the current assisted reproductive technologies (ARTs). Therefore, the present study aims to assess a series of parameters (follicles, oocytes, and embryos) and further by the outcomes in women following the administration of follitropin delta. Materials and methods: This observational study included 205 women. They were aged between 21 and 43 years (mean 33.45) and an anti-Müllerian hormone (AMH) level ranging from 0.11 to 16.00 ng/dL (mean 2.89). Results: In accordance with the established methodology and following the centralization of data, a total of fifty-eight pregnancies (28.29%) were achieved; forty-five (36.88%) were achieved in women under 35 years and thirteen (15.66%) in women above 35 years. These figures are positively correlated with women’s age considering that the number of follicles >18 mm, oocytes fertilized and embryo(s) varies among groups. Regarding the interest parameters, we noted n = 1719 follicles > 18 mm, n = 1279 retrieved oocytes, and n = 677 embryos at day 3. On the other hand, the following figures have been registered in women above 35 years: 814–follicles > 18 mm, 612 oocytes retrieved and 301 embryos at day 3. During this study, we registered only three cases of abortions (n = 1–0.81% in women under 35 years and n = 2–2.40% in women above 35 years). Nine pregnancies (7.37%) were stopped from evolution in females under 35 years, and twelve pregnancies (n = 8–6.55% in women under 35 years, while n = 4 in women above 35 years) were unsuccessful. A twin pregnancy has been confirmed (1.20%) in women above 35 years, six ongoing pregnancies (4.91%) in those under 35 years, and two in both groups (one per group–n = 1–0.81%, and 1.20%–n = 1) in which we did not know the exact result were registered at the end of the established studied interval. However, there were also situations in which the treatment cause an over-reactivity or had no effect; n = 2 were non-responders, and n = 1 exhibited moderate ovarian hyperstimulation syndrome (OHSS). Conclusions: Based on our results, we strongly encourage the use of this recombinant gonadotropin on a much larger scale.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1091
Author(s):  
Izaak Van Crombrugge ◽  
Rudi Penne ◽  
Steve Vanlanduit

Knowledge of precise camera poses is vital for multi-camera setups. Camera intrinsics can be obtained for each camera separately in lab conditions. For fixed multi-camera setups, the extrinsic calibration can only be done in situ. Usually, some markers are used, like checkerboards, requiring some level of overlap between cameras. In this work, we propose a method for cases with little or no overlap. Laser lines are projected on a plane (e.g., floor or wall) using a laser line projector. The pose of the plane and cameras is then optimized using bundle adjustment to match the lines seen by the cameras. To find the extrinsic calibration, only a partial overlap between the laser lines and the field of view of the cameras is needed. Real-world experiments were conducted both with and without overlapping fields of view, resulting in rotation errors below 0.5°. We show that the accuracy is comparable to other state-of-the-art methods while offering a more practical procedure. The method can also be used in large-scale applications and can be fully automated.


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