TY - CHAP A1 - Breuß, Michael A1 - Mansouri Yarahmadi, Ashkan ED - Durou, Jean-Denis ED - Falcone, Maurizio ED - Quéau, Yvain ED - Tozza, Silvia T1 - Perspective Shape from Shading : An Exposition on Recent Works with New Experiments T2 - Advances in Photometric 3D-Reconstruction N2 - Shape from Shading (SFS) is a fundamental task in computer vision. By given information about the reflectance of an object’s surface and the position of the light source, the SFS problem is to reconstruct the 3D depth of the object from a single grayscale 2D input image. A modern class of SFS models relies on the property that the camera performs a perspective projection. The corresponding perspective SFS methods have been the subject of many investigations within the last years. The goal of this chapter is to give an overview of these developments. In our discussion, we focus on important model aspects, and we investigate some prominent algorithms appearing in the literature in more detail than it was done in previous works. KW - Shape from Shading Perspective projection Hamilton Jacobi equations Numerical methods Fast marching method Y1 - 2020 SN - 978-3-030-51865-3 SN - 978-3-030-51866-0 U6 - https://doi.org/https://doi.org/10.1007/978-3-030-51866-0_2 SN - 2191-6586 SN - 2191-6594 SP - 31 EP - 72 PB - Springer CY - Cham ER - TY - GEN A1 - Mansouri Yarahmadi, Ashkan A1 - Breuß, Michael A1 - Hartmann, Carsten A1 - Schneidereit, Toni T1 - Unsupervised Optimization of Laser Beam Trajectories for Powder Bed Fusion Printing and Extension to Multiphase Nucleation Models T2 - Mathematical Methods for Objects Reconstruction : From 3D Vision to 3D Printing N2 - In laser powder bed fusion, it is known that the quality of printing results crucially depends on the temperature distribution and its gradient over the manufacturing plate. We propose a computational model for the motion of the laser beam and the simulation of the time-dependent heat evolution over the plate. For the optimization of the laser beam trajectory, we propose a cost function that minimizes the average thermal gradient and allows to steer the laser beam. The optimization is performed in an unsupervised way. Specifically, we propose an optimization heuristic that is inspired by the well-known traveling salesman problem and that employs simulated annealing to determine a nearly optimal pathway. By comparison of the heat transfer simulations of the derived trajectories with trajectory patterns from standard printing protocols we show that the method gives superior results in terms of the given cost functional. KW - Additive manufacturing Multiphase alloys Trajectory optimization Powder bed fusion printing Heat simulation Linear-quadratic control Y1 - 2023 SN - 978-981-99-0775-5 U6 - https://doi.org/10.1007/978-981-99-0776-2_6 SN - 978-981-99-0776-2 SP - 157 EP - 176 PB - Springer CY - Singapor ER - TY - GEN A1 - Mansouri Yarahmadi, Ashkan A1 - Breuß, Michael A1 - Khan Mohammadi, Mohsen T1 - Explaining StyleGAN Synthesized Swimmer Images in Low-Dimensional Space T2 - Computer Analysis of Images and Patterns : 20th International Conference, CAIP 2023, Limassol, Cyprus, September 25–28, 2023, Proceedings, Part I N2 - In many existing AI methods, the reasons behind the decisions made by a trained model are not easy to explain. This often leads to a black-box design that is not interpretable, which makes it a delicate issue to adopt such methods in an application related to safety. We consider generative adversarial networks that are often used to generate data for further use in deep learning applications where not much data is available. In particular, we deal with the StyleGAN approach for generating synthetic observations of swimmers. This paper provides a pipeline that can clearly explain the synthesized images after projecting them to a lower dimensional space. These understood images can later be chosen to train a swimmer safety observation framework. The main goal of our paper is to achieve a higher level of abstraction by which one can explain the variation of synthesized swimmer images in low dimension space. A standard similarity measure is used to evaluate our pipeline and validate a low intra-class variation of established swimmer clusters representing similar swimming style within a low dimensional space. Y1 - 2023 SN - 978-3-031-44236-0 U6 - https://doi.org/10.1007/978-3-031-44237-7_16 SN - 978-3-031-44237-7 SP - 164 EP - 173 ER - TY - GEN A1 - Mansouri Yarahmadi, Ashkan A1 - Breuß, Michael A1 - Hartmann, Carsten T1 - Long Short-Term Memory Neural Network for Temperature Prediction in Laser Powder Bed Additive Manufacturing T2 - Proceedings of SAI Intelligent Systems Conference N2 - n context of laser powder bed fusion (L-PBF), it is known that the properties of the final fabricated product highly depend on the temperature distribution and its gradient over the manufacturing plate. In this paper, we propose a novel means to predict the temperature gradient distributions during the printing process by making use of neural networks. This is realized by employing heat maps produced by an optimized printing protocol simulation and used for training a specifically tailored recurrent neural network in terms of a long short-term memory architecture. The aim of this is to avoid extreme and inhomogeneous temperature distribution that may occur across the plate in the course of the printing process. In order to train the neural network, we adopt a well-engineered simulation and unsupervised learning framework. To maintain a minimized average thermal gradient across the plate, a cost function is introduced as the core criteria, which is inspired and optimized by considering the well-known traveling salesman problem (TSP). As time evolves the unsupervised printing process governed by TSP produces a history of temperature heat maps that maintain minimized average thermal gradient. All in one, we propose an intelligent printing tool that provides control over the substantial printing process components for L-PBF, i.e. optimal nozzle trajectory deployment as well as online temperature prediction for controlling printing quality. KW - Additive manufacturing Laser beam trajectory optimization Powder bed fusion printing Heat simulation Linear-quadratic control Y1 - 2022 SN - 978-3-031-16074-5 U6 - https://doi.org/10.1007/978-3-031-16075-2_8 SN - 978-3-031-16075-2 SP - 119 EP - 132 PB - Springer CY - Cham ER - TY - CHAP A1 - Scheffler, Robert A1 - Mansouri Yarahmadi, Ashkan A1 - Breuß, Michael A1 - Köhler, Ekkehard ED - Pelillo, Marcello ED - Hancock, Edwin T1 - A Graph Theoretic Approach for Shape from Shading T2 - Energy minimization methods in computer vision and pattern recognition , 11th International Conference, EMMCVPR 2017, Venice, Italy, October 30 – November 1, 2017 N2 - Resolving ambiguities is a fundamental problem in shape from shading (SFS). The classic SFS approach allows to reconstruct the surface locally around singular points up to an ambiguity of convex, concave or saddle point type. In this paper we follow a recent approach that seeks to resolve the local ambiguities in a global graph-based setting so that the complete surface reconstruction is consistent. To this end, we introduce a novel graph theoretic formulation for the underlying problem that allows to prove for the first time in the literature that the underlying surface orientation problem is NP-complete. Moreover, we show that our novel framework allows to define an algorithmic framework that solves the disambiguation problem. It makes use of cycle bases for dealing with the graph construction and enables an easy embedding into an optimization method that amounts here to a linear program. KW - Shape from shading KW - Ambiguity KW - Configuration graph KW - Cycle basis Y1 - 2018 SN - 978-3-319-78198-3 U6 - https://doi.org/10.1007/978-3-319-78199-0_22 SP - 328 EP - 341 PB - Springer CY - Cham ER - TY - CHAP A1 - Breuß, Michael A1 - Mansouri Yarahmadi, Ashkan A1 - Cunningham, Douglas W. ED - Welk, Martin ED - Urschler, Martin ED - Roth, Peter M. T1 - The Convex-Concave Ambiguity in Perspective Shape from Shading T2 - Proceedings of the OAGM Workshop 2018 Medical Image Analysis, May 15 - 16, 2018, Hall/Tyrol, Austria N2 - Shape from Shading (SFS) is a classic problem in computer vision. In recent years many perspective SFS models have been studied that yield useful SFS approaches when a photographed object is close to the camera. However, while the ambiguities inherent to the classical, orthographic SFS models are well-understood, there has been no discussion of possible ambiguities in perspective SFS models. In this paper we deal with the latter issue. Therefore we adopt a typical perspective SFS setting. We show how to transform the corresponding image irradiance equation into the format of the classical orthographic setting by employing spherical coordinates. In the latter setting we construct a convex-concave ambiguity for perspective SFS. It is to our knowledge the first time in the literature that this type of ambiguity is constructed and verified for a perspective SFS model. KW - Shape from Shading Y1 - 2018 SN - 978-3-85125-603-1 U6 - https://doi.org/10.3217/978-3-85125-603-1-13 SP - 57 EP - 63 PB - Verlag der TU Graz CY - Graz ER - TY - GEN A1 - Breuß, Michael A1 - Buhl, Johannes A1 - Mansouri Yarahmadi, Ashkan A1 - Bambach, Markus A1 - Peter, Pascal T1 - A Simple Approach to Stiffness Enhancement of a Printable Shape by Hamilton-Jacobi Skeletonization T2 - Procedia Manufacturing N2 - The 3D-Printing technology is ready to produce parts with specific properties like individual stiffness. Based on a predefined outer shape, the inner structure of a printed part defines mainly the mechanical features. By Hamilton-Jacobi skeletonization, a stiffness enhancement of a printable shape can be achieved in a way, that a novel AM-corner includes linear axis function. Originating in the field of shape analysis in computer vision and graphics, the so-called medial axis transform (MAT) is designed for the computation of a structure that resembles the bone structure of biological shapes. The input for MAT computation is typically a shape’s boundary. The arising topological skeletons have proven to provide a useful concept for many applications; however, their computation is generally intricate and also known to rely on many parameters, diminishing the accessibility of skeletonization methods. In this work, the classical Hamilton-Jacobi skeletonization approach is adopted to compute a stability enhancing shape structure. As the basic method has not been designed for the context of additive manufacturing, a set of suitable modifications are introduced to design an algorithm that suits our intended purpose. Unlike the traditional skeletonization schemes, the resulting method appears to be robust and in practice almost completely automated as we can identify useful generic parameter settings. By a finite element method (FEM) study, the elastic stress properties of the AM-corner with linear axis function is validated and printed with in metal (1.4404) with the 3D Selected Laser Melting (SLM) system AconityMIDI. The AM-knot with skeletonization guides approximately 20 times better than a standard knot. While the first obtained results are shown as 2.5 dimensional shapes, it is emphasized that the proposed algorithm offers many possibilities for extensions to three dimensions and variations in context of additive manufacturing. KW - Skeletonization KW - Hamilton-Jacobi skeletonization KW - stiffness enhancement KW - 3D printing KW - additive manufacturing Y1 - 2020 U6 - https://doi.org/10.1016/j.promfg.2020.04.147 SN - 2351-9789 N1 - 23rd International Conference on Material Forming (ESAFORM 2020) VL - Vol. 47 SP - 1190 EP - 1196 ER - TY - GEN A1 - Radow, Georg A1 - Rodriguez, Giuseppe A1 - Mansouri Yarahmadi, Ashkan A1 - Breuß, Michael ED - Cristiani, Emiliano T1 - Photometric Stereo with Non-Lambertian Preprocessing and Hayakawa Lighting Estimation for Highly Detailed Shape Reconstruction T2 - Mathematical Methods for Objects Reconstruction : From 3D Vision to 3D Printing N2 - In many realistic scenarios, the use of highly detailed photometric 3D reconstruction techniques is hindered by several challenges in given imagery. Especially, the light sources are often unknown and need to be estimated, and the light reflectance is often non-Lambertian. In addition, when approaching the problem to apply photometric techniques at real-world imagery, several parameters appear that need to be fixed in order to obtain high-quality reconstructions. In this chapter, we attempt to tackle these issues by combining photometric stereo with non-Lambertian preprocessing and Hayakawa lighting estimation. At hand of a dedicated study, we discuss the applicability of these techniques for their use in automated 3D geometry recovery for 3D printing. KW - Photometric stereo Shape from shading Hayakawa procedure Lighting estimation Oren-Nayar model Lambertian reflector Y1 - 2023 SN - 978-981-99-0775-5 U6 - https://doi.org/10.1007/978-981-99-0776-2_2 SN - 978-981-99-0776-2 SN - 2281-518X SP - 35 EP - 56 PB - Springer CY - Singapore ER - TY - GEN A1 - Mansouri Yarahmadi, Ashkan A1 - Breuß, Michael T1 - Automatic Watermeter Reading in Presence of Highly Deformed Digits T2 - Computer Analysis of Images and Patterns N2 - The task we face in this paper is to automate the reading of watermeters as can be found in large apartment houses. Typically water passes through such watermeters, so that one faces a wide range of challenges caused by water as the medium where the digits are positioned. One of the main obstacles is given by the frequently produced bubbles inside the watermeter that deform the digits. To overcome this problem, we propose the construction of a novel data set that resembles the watermeter digits with a focus on their deformations by bubbles. We report on promising experimental recognition results, based on a deep and recurrent network architecture performed on our data set. KW - Underwater digit recognition / Sequence models / Connectionist Temporal Classification Y1 - 2021 SN - 978-3-030-89130-5 U6 - https://doi.org/10.1007/978-3-030-89131-2_14 SN - 978-3-030-89131-2 SP - 153 EP - 163 PB - Springer CY - Cham ER - TY - GEN A1 - Breuß, Michael A1 - Sharifi Boroujerdi, Ali A1 - Mansouri Yarahmadi, Ashkan T1 - Modelling the Energy Consumption of Driving Styles Based on Clustering of GPS Information T2 - Modelling N2 - This paper presents a novel approach to distinguishing driving styles with respect to their energy efficiency. A distinct property of our method is that it relies exclusively on the global positioning system (GPS) logs of drivers. This setting is highly relevant in practice as these data can easily be acquired. Relying on positional data alone means that all features derived from them will be correlated, so we strive to find a single quantity that allows us to perform the driving style analysis. To this end we consider a robust variation of the so-called "jerk" of a movement. We give a detailed analysis that shows how the feature relates to a useful model of energy consumption when driving cars. We show that our feature of choice outperforms other more commonly used jerk-based formulations for automated processing. Furthermore, we discuss the handling of noisy, inconsistent, and incomplete data, as this is a notorious problem when dealing with real-world GPS logs. Our solving strategy relies on an agglomerative hierarchical clustering combined with an L-term heuristic to determine the relevant number of clusters. It can easily be implemented and delivers a quick performance, even on very large, real-world datasets. We analyse the clustering procedure, making use of established quality criteria. Experiments show that our approach is robust against noise and able to discern different driving styles KW - clustering KW - energy efficiency KW - driving style analysis KW - jerk-based feature KW - Gjerk-based feature KW - PS data Y1 - 2022 U6 - https://doi.org/10.3390/modelling3030025 SN - 2673-3951 VL - 3 IS - 3 SP - 385 EP - 399 ER - TY - GEN A1 - Schneidereit, Slavomira A1 - Mansouri Yarahmadi, Ashkan A1 - Schneidereit, Toni A1 - Breuß, Michael A1 - Gebauer, Marc T1 - YOLO- based Object detection in industry 4.0 Fischertechnik Model Environment T2 - Computer Science > Computer Vision and Pattern Recognition, Intelligent Systems Conference 2023 (IntelliSys 2023) N2 - In this paper we extensively explore the suitability of YOLO architectures to monitor the process flow across a Fischertechnik industry 4.0 application. Specifically, different YOLO architectures in terms of size and complexity design along with different prior-shapes assignment strategies are adopted. To simulate the real world factory environment, we prepared a rich dataset augmented with different distortions that highly enhance and in some cases degrade our image qualities. The degradation is performed to account for environmental variations and enhancements opt to compensate the color correlations that we face while preparing our dataset. The analysis of our conducted experiments shows the effectiveness of the presented approach evaluated using different measures along with the training and validation strategies that we tailored to tackle the unavoidable color correlations that the problem at hand inherits by nature. Y1 - 2023 U6 - https://doi.org/10.48550/arXiv.2301.12827 ER -