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作者： Chen, Ziwei Lyu, Desheng School of Architecture Harbin Institute of Technology Harbin China Key Laboratory of Interactive Media Design and Equipment Service Innovation Ministry of Culture and Tourism of the People's Republic of China Harbin China

Virtual pavilions can help spread culture and bring fun. A virtual pavilion needs a designed map, and terrain editors then manually layout each part of it. Procedural content generation via machine learning can quickly generate virtual pavilion maps to assist in virtual pavilion design. This article proposes adding a self-attention module to some commonly used deep convolutional generative adversarial networks to generate virtual pavilion maps. A three-dimensional(3D) virtual pavilion is built based on these maps, and interactive features are added to make it more experiential. Then the improved and original networks are mainly evaluated in generating maps that are solvable and similar to the training data for finding the best generator. The evaluation results show that our improved methods always perform better on each metric, and the WGAN with a self-attention module is what we need. © 2022 John Wiley & Sons, Ltd.

关键词： Generative adversarial networks

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Technologies and Techniques for Collaborative Robotics in architecture 25

Technologies and Techniques for Collaborative Robotics in Ar...

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25th International Conference on Computer-Aided Architectural design Research in Asia, CAADRIA 2020

作者： Jensen, Mads Brath Das, Avishek Department of Architecture Design and Media Technology

ISBN: (纸本)9789887891741

This study investigates the technological and methodological challenges in establishing an indeterministic approach to robotic fabrication that allows for a collaborative and creative design/fabrication process. The research objective enquires into how robotic processes in architecture can move from deterministic fabrication processes towards explorative and indeterministic design processes. To address this research objective, the study specifically explores how an architect and a robot can engage in a process of co-creation and co-evolution, that is enabled by a collaborative robotic arm equipped with an electric gripper and a web camera. Through a case-based experiment, of designing and constructing an adjustable facąde system consisting of parallel wood lamellas, designer and robotic system co-create by means of interactive processes. The study will present and discuss the technological implementations used to construct the interactive robotic-based design process, with emphasis on the integration of visual analysis features in Grasshopper and on the benefits of establishing a state machine for interactive and creative robotic control in architecture. © 2020 and published by the Association for Computer-Aided Architectural design Research in Asia (CAADRIA), Hong Kong.

关键词： Human computer interaction

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Semantic Segmentation of Golf Courses for Course Rating Assistance

Semantic Segmentation of Golf Courses for Course Rating Assi...

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IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

作者： Jesper Kjærgaard Mortensen Vinicius Soares Matthiesen Jacobo González de Frutos Kata Bujdosó Jesper Thøger Christensen Andreas Møgelmose Department of Electronic Systems Aalborg Univeristy Aalborg Denmark Department of Architecture Design and Media Technology Aalborg University Aalborg Denmark

This paper introduces a system to assist golf course raters in determining the difficulty rating of a golf hole. Currently, determining the rating of a given golf hole relies on time-consuming manual measurements on the ground, which we attempt to partially automate. A U - net neural network is trained to classify greens, fairways, tees, bunkers, and water in golf courses, and a course rating assistance system is implemented to measure distances between relevant course parts. Since no public datasets containing golf courses existed prior to this work, we present a new public data set of golf courses created from orthophotos. 1,123 RGB orthophotos for training/validation and 108 RGB orthophotos for testing were gathered from 107 Danish golf courses (58 % of Danish courses) during the spring season and manually annotated. The dataset is publicly available on Kaggle 1 1 https://***/datasets/jacotaco/danish-golf-courses-orthophotos. The U-net model accomplished a mean intersection over union (IoU) of 69.6%, mean sensitivity of 78.0%, and mean positive predictive value (PPV) of 84.1 %. Based on this automatic analysis of the course images, the course rating assistance system computes 5 crucial distances for course raters to determine a course rating and achieved a mean error of 2.7% and 17.7 % for green length and width, as well as a mean error of 3.3 % and 4.2 % for male/female hole lengths.

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A research infrastructure for generating and sharing diversity-aware data

arXiv

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arXiv 2023年

作者： Busso, Matteo Abente Acosta, Ronald Chenu De Götzen, Amalia Department of Information Engineering and Computer Science University of Trento Italy Department of Architecture Design and Media Technology Aalborg University Denmark

The intensive flow of personal data associated with the trend of computerizing aspects of people’s diversity in their daily lives is associated with issues concerning not only people protection and their trust in new technologies, but also bias in the analysis of data and problems in their management and reuse. Faced with a complex problem, the strategies adopted, including technologies and services, often focus on individual aspects, which are difficult to integrate into a broader framework, which can be of effective support for researchers and developers. Therefore, we argue for the development of an end-to-end research infrastructure (RI) that enables trustworthy diversity-aware data within a citizen science community. © 2023, CC BY-NC-ND.

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Fall Detection in Hospital Rooms with Probabilistic Graphical Models

Fall Detection in Hospital Rooms with Probabilistic Graphica...

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Workshops on Image Processing Theory, Tools and Applications, IPTA

作者： Jacobo González de Frutos Mia Sandra Nicole Siemon Kamal Nasrollahi Dept. of Electronic Systems Aalborg University Aalborg Denmark Dept. of Architecture Design and Media Technology Aalborg University and Milestone Systems Aalborg Denmark

ISBN: (数字)9798331541842

ISBN: (纸本)9798331541859

Unintentional injury deaths, primarily caused by simple falls among elderly individuals, have consistently ranked as the second most common cause of death over the years, as documented by the World Health Organization. This not only poses a significant health concern but also imposes a substantial financial burden on hospitals, as insurance companies typically do not cover such events. This project aims to address this challenge by developing a simple Artificial Intelligence system based on Video Anomaly Detection to detect fall situations that require less computational power and protect patients' privacy. The system comprises a Keypoint Detector for estimating the patient's pose and a discrete Bayesian Network to detect whether a person has fallen or not. The approach has been trained and tested under the public dataset CAUCAFall achieving an average accuracy of 90.62%, Area Under the ROC Curve of 88.71%, Region-Based Detection Criterion of 86.23% and Track-Based Detection Criterion of 98.39%. The obtained results demonstrate highly competitive performance, approaching the levels achieved by the most recent State-of-the-art works tested on CAUCAFall. Our unsupervised methodology to fall detection is privacy-preserving, computationally lightweight, and learns patterns from the training data in seconds on a conventional 30GB memory Google Cloud Virtual Machine with 8 AMD EPYC 7B13s Intel Broadwell CPUs.

关键词： Privacy Graphical models Hospitals Image processing Training data Insurance Probabilistic logic Fall detection Older adults Injuries

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An Augmented Reality Training Application for Service and Maintenance of a Medical Analyzer: A UX Approach to Usefulness and User Satisfaction

An Augmented Reality Training Application for Service and Ma...

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Immersive Learning Research Network (iLRN), Conference of the

作者： Liana-Dorina Mø sbæ k Thomas Bjø rner Dept. of Architecture Design and Media Technology Aalborg University Copenhagen Denmark

This paper presents an experimental study on a mobile augmented reality application for immersive training of field engineers in service and maintenance of a medical analyzer (AQT90FLEX). Based on approaches from user experience design, we developed an AR training application with the aim of high level of relevance, ease of use, usefulness, user satisfaction, and learnability. Sixteen field engineers from the multinational company Radiometer participated in the study. The procedure was divided into three iterative stages: design, prototype, and evaluation. The methods consisted of questionnaires, interviews, and co-creation. The questionnaire was inspired by the technology acceptance model. The findings revealed that all the field engineers expressed positive feedback in terms of being able to see, train, and practice on the AQT90FLEX analyzer. Especially the usefulness and user satisfaction were positively evaluated. This study also shows the importance of using mixed methods, both qualitative and quantitative approaches, in order to develop an AR training application for field engineers across the world.

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Evaluation of Edge Platforms for Deep Learning in Computer Vision 25th

Evaluation of Edge Platforms for Deep Learning in Computer V...

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25th International Conference on Pattern Recognition Workshops, ICPR 2020

作者： Rasmussen, Christoffer Bøgelund Lejbølle, Aske Rasch Nasrollahi, Kamal Moeslund, Thomas B. Department of Architecture Design and Media Technology Aalborg University Aalborg Denmark Research Department of Milestone Systems Copenhagen Denmark

ISBN: (纸本)9783030687984

In recent years, companies, such as Intel and Google, have brought onto the market small low-power platforms that can be used to deploy and run inference of Deep Neural Networks at a low cost. These platforms can process data at the edge, such as images from a camera, to avoid transfer of large amount of data across a network. To determine which platform to use for a specific task, practitioners usually compare parameters, such as inference time and power consumption. However, to provide a better incentive on platform selection based on requirements, it is important to also consider the platform price. In this paper, we explore platform/model trade-offs, by providing benchmarks of state-of-the-art platforms within three common computer vision tasks;classification, detection and segmentation. By also considering the price of each platform, we provide a comparison of price versus inference time, to aid quick decision making in regard to platform and model selection. Finally, by analysing the operation allocation of models for each platform, we identify operations that should be optimised, based on platform/model selection. © 2021, Springer Nature Switzerland AG.

关键词： Computer vision

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Seasonal Sunlight Chamber: A Lighting design Concept to Connect Us to the Dynamics of Sunlight and Our Place on Earth 5th

Seasonal Sunlight Chamber: A Lighting Design Concept to Conn...

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5th EAI International Conference on design, Leaning and Innovation, DLI 2020

作者： Strebel, Emma Hansen, Ellen Kathrine Lighting Design Department of Architecture Design and Media Technology Aalborg University A. C. Meyers Vænge 15 Copenhagen2450 Denmark

ISBN: (纸本)9783030784478

People currently exist mainly indoors, detached from their natural surroundings. During times of rapid growth, globalization and digitalization, it has never been more important to investigate how to reconnect to our natural environment. In this paper we develop a design to investigate how a lighting design concept can act as a tool to understand the geometry of sunlight on Earth and thereby meet human needs to be in touch with the environment. A design is developed by redefining an ancient analogue technology, the sundial. The path of the Sun is translated into a design concept and is demonstrated in a three dimensional time and sight specific prototype. This design concept creates embodied experiences where viewers interact with their ever-changing daylight and surroundings. The aim with this exploratory design is to create a visual tool for learning about complex natural phenomena and understanding our relation to Earth and the Sun. It thereby discusses how a design can put humans in touch with their natural surroundings to satisfy individual biological needs in order to better understand contemporary environmental needs at large. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Lighting

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Contemplative neuroaesthetics and architecture:A sensorimotor exploration

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Frontiers of Architectural Research 2024年第1期13卷 97-111页

作者： Zakaria Djebbara Juliet King Amir Ebadi Yoshio Nakamura Julio Bermudez Department of Architecture DesignMediaand TechnologyAalborg UniversityAalborgDenmark Biopsychology und Neuroergonomy Technical University BerlinBerlinGermany Art Therapy Department The George Washington UniversityWashington DCUnited States Department of Neurology Indiana University School of MedicineIndianapolisUnited States Dellustration Washington DCUnited States Pain Research Center Division of Pain MedicineDepartment of AnesthesiologyUniversity of Utah School of MedicineUtahUnited States School of Architecture and Planning The Catholic University of AmericaWashington DCUnited States

This paper takes initial steps towards developing a theoretical framework of contemplative neuroaesthetics through sensorimotor *** first argue that this new area has been largely omitted from the contemporary research agenda in neuroaesthetics and thus remains a domain of untapped *** seek to define this domain to foster a clear and focused investigation of the capacity of the arts and architecture to induce phenomenological states of a contemplative *** proposing a sensorimotor account of the experience of architecture,we operationalize how being attuned to architecture can lead to contemplative *** contrasting the externally-induced methods with internally-induced methods for eliciting a contemplative state of mind,we argue that architecture may spontaneously and effortlessly lead to such states as certain built features naturally resonate with our sensorimotor *** suggest that becoming sensible of the resonance and attunement process between internal and external states is what creates an occasion for an externallyinduced contemplative ***,we review neuroscientific studies of architecture,elaborate on the brain regions involved in such aesthetic contemplative responses,provide architectural examples,and point at the contributions that this new area of inquiry may have in fields such as the evidence-based design movement in architecture.

关键词： Neuropheno menology Neuroaesthetics Contemplative states Architectural experience Well-being

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Real-Time Face Mask Detection with Deep Learning for Pandemic Safety

Real-Time Face Mask Detection with Deep Learning for Pandemi...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Chudanat Sudthongkhong Budsakayt Intarapasan Thitima Wongsheree Kejkaew Thanasuan Bennapa Pattanapipat Putawan Suksai Department of Medical and Science Media School of Architecture and Design King Mongkut’s University of Technology Thonburi (KMUTT) Bangkok Thailand Interior Architecture Program School of Architecture and Design King Mongkut’s University of Technology Thonburi (KMUTT) Bangkok Thailand Institue for Scientific and Technology Research and Services King Mongkut’s University of Technology Thonburi (KMUTT) Bangkok Thailand Department of Media Technology School of Architecture and Design King Mongkut’s University of Technology Thonburi (KMUTT) Bangkok Thailand The Faculty of Mass Communication Technology Rajamangala University of Technology Rattanakosin (RMUTT) Bangkok Thailand

Amid the COVID-19 pandemic, efficient screening of individuals has become imperative. Our project aims to develop an automated system that combines Computer Vision, Infrared Thermometer sensors, and Data Analytics to streamline This process while ensuring public safety. Our objectives encompass designing and implementing an automated screening system, improving data handling and storage, and rigorously testing system efficiency. This system surpasses traditional temperature gauges with a remarkable 93.67% accuracy and excels in detecting sanitary mask compliance with a rate of 96.78%. Additionally, it contributes to environmental sustainability by completely eliminating outdoor waste generation. The user-friendly interface and systematic data storage in a database enable retrospective analysis and efficient data management. Expert assessments and performance tests ensure the system’s quality and practicality. In summary, our project introduces an automated system that enhances user screening during the COVID-19 outbreak, offering high accuracy, efficiency, and data management capabilities. This system plays a crucial role in safeguarding public health and community well-being. In the future research, the accuracy results comparison between this method and other methods will be report in the next conference.

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