Reconstructing Signing Avatars from Video Using Linguistic Priors

Sign language (SL) is the primary method of communication for the 70 million Deaf people around the world. Video dictionaries of isolated signs are a core SL learning tool. Replacing these with 3D avatars can aid learning and enable AR/VR applications, improving access to technology and online media. However, little work has attempted to estimate expressive 3D avatars from SL video; occlusion, noise, and motion blur make this task difficult. We address this by introducing novel linguistic priors that are universally applicable to SL and provide constraints on 3D hand pose that help resolve ambiguities within isolated signs. Our method, SGNify, captures fine-grained hand pose, facial expression, and body movement fully automatically from in-the-wild monocular SL videos. We evaluate SGNify quantitatively by using a commercial motion-capture system to compute 3D avatars synchronized with monocular video. SGNify outperforms state-of-the-art 3D body-pose- and shape-estimation methods on SL videos. A perceptual study shows that SGNify's 3D reconstructions are significantly more comprehensible and natural than those of previous methods and are on par with the source videos. Code and data are available at sgnify.is.tue.mpg.de

3D Human Pose Estimation via Intuitive Physics

Estimating 3D humans from images often produces implausible bodies that lean, float, or penetrate the floor. Such methods ignore the fact that bodies are typically supported by the scene. A physics engine can be used to enforce physical plausibility, but these are not differentiable, rely on unrealistic proxy bodies, and are difficult to integrate into existing optimization and learning frameworks. In contrast, we exploit novel intuitive-physics (IP) terms that can be inferred from a 3D SMPL body interacting with the scene. Inspired by biomechanics, we infer the pressure heatmap on the body, the Center of Pressure (CoP) from the heatmap, and the SMPL body's Center of Mass (CoM). With these, we develop IPMAN, to estimate a 3D body from a color image in a "stable" configuration by encouraging plausible floor contact and overlapping CoP and CoM. Our IP terms are intuitive, easy to implement, fast to compute, differentiable, and can be integrated into existing optimization and regression methods. We evaluate IPMAN on standard datasets and MoYo, a new dataset with synchronized multi-view images, ground-truth 3D bodies with complex poses, body-floor contact, CoM and pressure. IPMAN produces more plausible results than the state of the art, improving accuracy for static poses, while not hurting dynamic ones. Code and data are available for research at https://ipman.is.tue.mpg.de.Comment: Accepted in CVPR'23. Project page: https://ipman.is.tue.mpg.d

Cellular Automata Applications in Shortest Path Problem

Cellular Automata (CAs) are computational models that can capture the essential features of systems in which global behavior emerges from the collective effect of simple components, which interact locally. During the last decades, CAs have been extensively used for mimicking several natural processes and systems to find fine solutions in many complex hard to solve computer science and engineering problems. Among them, the shortest path problem is one of the most pronounced and highly studied problems that scientists have been trying to tackle by using a plethora of methodologies and even unconventional approaches. The proposed solutions are mainly justified by their ability to provide a correct solution in a better time complexity than the renowned Dijkstra's algorithm. Although there is a wide variety regarding the algorithmic complexity of the algorithms suggested, spanning from simplistic graph traversal algorithms to complex nature inspired and bio-mimicking algorithms, in this chapter we focus on the successful application of CAs to shortest path problem as found in various diverse disciplines like computer science, swarm robotics, computer networks, decision science and biomimicking of biological organisms' behaviour. In particular, an introduction on the first CA-based algorithm tackling the shortest path problem is provided in detail. After the short presentation of shortest path algorithms arriving from the relaxization of the CAs principles, the application of the CA-based shortest path definition on the coordinated motion of swarm robotics is also introduced. Moreover, the CA based application of shortest path finding in computer networks is presented in brief. Finally, a CA that models exactly the behavior of a biological organism, namely the Physarum's behavior, finding the minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201

Supplier selection problem in fuzzy environment considering risk factors

Supplier selection is one of the most important and challenging issue in supply chain management and is usually tackled with multi-criteria decision making (MCDM) methods. Considering sustainability, the complexity of the supplier selection problem has increased in recent years, yet, the various sustainability criteria. However, these criteria are usually considered independent of each other. Therefore, in this paper, to take into account the interdependency among criteria, Fuzzy Cognitive Maps (FCM) have been used. Moreover, supply chains are susceptible to various endogenous and exogenous risks which need to be considered in the decision-making processes in order to meet market needs and sustainability requirements. In order to integrate risks into the decision problem, fuzzy axiomatic design approach with risk factors (RFAD) has been utilized. The proposed method is applied to a case study adapted from literature. © 2019 IEEE

A multi-agent based decision framework for sustainable supplier selection, order allocation and routing problem

Supply chain decisions should aim for sustainability, in order to meet the global market needs, as well as the Industry 4.0 requirements, therefore they should consider beyond economic and environmental, societal dimensions as well. The complexity in decision making increases, moreover, supply network relationships become important, including inter-relationships and those developed with the suppliers. Agent technology is compatible with Industry 4.0, whereas multi-agent systems (MAS) can provide decision support for supply chain management and model the relatationships and interactions between entities in the supply chain environment. Therefore, in this paper, a MAS-based framework is proposed to address sustainability focused decision making in supplier selection, order allocation and routing. Fuzzy Multi Criteria Decision Making (MCDM) approaches and multi-objective programming are used by the agents in the MAS in order to adress sustainability requirements. Futrhermore, developed agent services for the supply chain business processes are integrated with web services, in order to facilitate business process execution as web services. © 2019 by SCITEPRESS - Science and Technology Publications, Lda

settlement siting

The refugee crisis resulted in a large influx of refugees in the Mediterranean since 2014. However, crises are inherently complex phenomena, whereas the ultimate goal of all involved actors is to provide humanitarian aid to the affected populations. The required supply chain management and logistics operations are characterized by complex decision making whereas coordination between involved actors is necessary for effective aid delivery. Therefore, distributed problem solving based on autonomous and interacting agent can be used as a decision support tool in this field. The purpose of this paper is to address the solution of the refugee settlement site planning problem with an intelligent multi-agent system (MAS) modeling method. In particular, intelligent agents use two well-known multi-criteria decision-making methods (MCDM), Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy axiomatic design approach with risk factors (RFAD), to rank alternative sites for refugee settlement siting. Up to authors' knowledge, this study is the first that utilizes MAS and MCDM approaches in a decision support system for refugee settlement planning in literature. The proposed method has been applied to evaluate four currently operating refugee accommodation sites in Greece. Obtained results have confirmed and reflected the current situation in these camp locations

Assessing the strength of democratic institutions associated with modern universities: the case of the Greek university

This paper proposes the establishment of a systematic framework for measuring dimensions of democracy within a university. It is shown that certain indicators internationally established and validated for the measurement of the institutional characteristics of democracy can, through appropriate adaptation, be transferred to the university field. A new model of mapping these characteristics to the university field was built using all available knowledge from international surveys, valid databases and researches conducted using questionnaires and structured interviews, specifically for the purposes of this paper. Chord diagrams, capable of providing meaningful dynamic graphical representations, were employed as a novel evaluative tool that highlights the existence and degree of significant interrelations between democracy indicators and democratic characteristics of the university. As a case study, we have chosen to analyze, compare and contrast the three most representative laws governing the operation of Greek universities for the last 35 years using the proposed model. Its operation, validity and capabilities were verified, after encapsulating the complex interdependencies among its variables, for a large time period, influenced by adverse social and economic changes. Thus, it can be used as an effective tool for comparisons among different universities, with respect to their democratic constitution. © 2020, The European Higher Education Society

A multi-agent based decision framework for sustainable supplier selection, order allocation and routing problem

Supply chain decisions should aim for sustainability, in order to meet the global market needs, as well as the Industry 4.0 requirements, therefore they should consider beyond economic and environmental, societal dimensions as well. The complexity in decision making increases, moreover, supply network relationships become important, including inter-relationships and those developed with the suppliers. Agent technology is compatible with Industry 4.0, whereas multi-agent systems (MAS) can provide decision support for supply chain management and model the relatationships and interactions between entities in the supply chain environment. Therefore, in this paper, a MAS-based framework is proposed to address sustainability focused decision making in supplier selection, order allocation and routing. Fuzzy Multi Criteria Decision Making (MCDM) approaches and multi-objective programming are used by the agents in the MAS in order to adress sustainability requirements. Futrhermore, developed agent services for the supply chain business processes are integrated with web services, in order to facilitate business process execution as web services. © 2019 by SCITEPRESS - Science and Technology Publications, Lda