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Issue 1

Visit the new journal website to submit and consult our contents: https://publications.eai.eu/index.php/ct/index

Editor(s)-in-Chief: Predrag K. Nikolic

EAI Endorsed Transactions on Creative Technologies is open access, a peer-reviewed scholarly journal focused on a whole industrial project or framework integrating creative technologies, creative content management, and more. The journal publishes research articles, review articles, commentaries, editorials, technical articles, and short communications with a quarterly frequency (four issues per year). Authors are not charged for article submission and processing.

The journal is not limited to only specific aspects of creative technologies but also open to considering the high-level and innovative contributions from a wide range of subfields, especially articles of interdisciplinary nature.

Some of the journal topics are:

Creative Industries - the paper can describe a whole industrial project or framework integrating creative technologies for domains such as:

  • Creative content providers: TV & radio (broadcast, linked media), fashion (RFID and sensors, energy recycling), music & movies, books (digitization, sonification), museums (creative/artistic installations for tourism or cultural heritage) and media archives, etc.
  • Creative services providers: Advertising (user-centered web and ads optimization), design (communication devices for creative environments), architecture (places that adapt to people, creativity from domotics), new media and transmedia, etc.
  • Creative experience providers: Movies and music experience, game-based installations and playable media (participative creation, DJs and VJs creative tools), interactive social and urban spaces, etc.

Scientific topics - the paper can focus on scientific tools for creative industries on topics such as:

  • Creative content management: Multimedia data mining and innovative browsing, data 2D/3D visualization, digitization and storage, cultural heritage, etc.
  • Creative interactions: Social signal processing, verbal and nonverbal, explicit or implicit interactions, interacting robots, sensors and MoCap, human-computer interaction, user interface design, serious game etc.
  • Creative experiences: Affective content analysis and synthesis, immersive technologies, special effects, augmented reality, expressivity and emotion detection and processing, user experiences, etc.

Additional materials such as videos of installations and setups, public/users reactions and comments, or demo links are welcome.

Call for Papers: ICDM 2021 (Manuscript submission deadline: 2021-10-15; Notification of acceptance: 2021-12-10; Submission of final revised paper: 2022-01-21; Publication of special issue (tentative): 2022-02-04)

Lead Guest Editor: Prof Dr. Mohd Shahrizal Sunar (Universiti Teknologi Malaysia) Guest Editor: Dr. Goh Eg Su (Universiti Teknologi Malaysia) Guest Editor: Ruhiyati Idayu Abu Talib (Universiti Teknologi Malaysia)

  • Albert Ali Salah (Bogazici University, Turkey)
  • Anthony Brooks (SensoramaLab, Aalborg University Esbjerg, Denmark)
  • Anton Nijholt (University of Twente, Netherlands)
  • Antonio Camurri (DIST-University of Genova, Italy)
  • Antonio Camurri (University of Genoa, Italy)
  • Christophe d'Alessandro (LIMSI-CNRS, France)
  • Christophe Hurter (ENAC, French Civil Aviation University, Toulouse France)
  • Cristina Sylla (University of Minho, Portugal)
  • Dirk Heylen (University of Twente, Netherlands)
  • Eva Irene (Aalborg University, Denmark)
  • Fabrizio Lamberti (Politecnico di Torino, Italy)
  • Gualtiero Volpe (University of Genoa, Italy)
  • Insook Choi (Columbia College Chicago, USA)
  • Jesus Ibanez (Escola Municipal d'Art i Disseny (EMAiD), Spain)
  • Jonathan Duckworth (RMIT University, Australia)
  • Jorge C. S. Cardoso (University of Coimbra, Portugal)
  • Jun Hu (Eindhoven University of Technology, Netherlands)
  • Lau Bee Theng (Swinburne University of Technology Sarawak Campus, Malaysia)
  • Mel Krokos (University of Portsmouth, United Kingdom)
  • Michail Kalogiannakis (Faculty of Education, University of Crete, Greece)
  • Milton Luiz Horn Vieira (Federal University of Santa Catarina, Brazil)
  • Mikkel Kirkedahl Lysholm Nielsen (Aalborg University, Denmark)
  • Pedro Campos (ITI/Larsys, University of Madeira, Funchal, Portugal)
  • Pieter Jan Maes (McGill University, Canada)
  • Rainer Malaka (University of Bremen, Germany)
  • Radu-Daniel Vatavu (University of Suceava, Romania)
  • Robin Bargar (Columbia College Chicago, USA)
  • Robby van Delden (University of Twente, Netherlands)
  • Sudarshan Khanna (National Institute of Design, India)
  • Surabhi Khanna (National Institute of Design Haryana, India)
  • Thierry Dutoit (University of Mons, Belgium)
  • Tiago Cardoso (University Nova of Lisbon, Portugal)
  • Tracy Harwood (De Montfort University, Leicester, United Kingdom)
  • Vincent Courboulay (University of La Rochelle, France)
  • Valentina Nisi (University of Madeira, Portugal)
  • Yves Rybarczyk (University Nova of Lisbon, Portugal)
  • Mohd Shahrizal Sunar (Universiti Teknologi, Malaysia)

  • AI_deation: A Creative Knowledge Mining Method for Design Exploration

    Appears in:
    ct 22(3): e5

    Authors:
    George Palamas, Liana-Dorina Møsbæk, Alejandra Mesa Guerra

    Published:
    23rd Nov 2022

    Abstract:
    Ideation is a core activity in the design process which begins with a design brief and results in a range of design concepts. However, due to its exploratory nature it is challenging to formalise computationally. Here, we report a creative knowledge mining method that combines design theory with a machine learning approach. This study begins by introducing a graphic design style classification model that acts as a model for the aesthetic evaluation of images. A Grad-CAM technique is used to visualise where our model is looking at in order to detect and interpret visual syntax, such as geometric influences and color gradients, to determine the most influential visual semiotics. Our comparative analysis on two Nordic design referents suggests that our approach can be efficiently used to support and motivate design exploration. Based on these findings, we discuss the prospects of machine vision aided design systems to envisage concepts and possible design paths, but also to support educational objectives.

  • Techniques For Reducing Energy And Delay For Data Aggregation In Wireless Sensor Networks

    Appears in:
    ct 22(3): e4

    Authors:
    Tao Feng, Muhammad Shoaib Akhtar

    Published:
    11th Oct 2022

    Abstract:
    WSN have many applications in different fields like medical, military, health and agriculture, etc., due to its data sensing and gathering abilities to Base station. The main issue in wireless sensor network is energy efficiency under consideration of QOS parameter like delay and security. Many of techniques have been proposed in literature but few work on energy efficient network with QOS. Due to lack of prior research in this area of study, this research will optimize the existing result in manner of giving efficient energy mechanisms and will also provide QOS as well as reduction of delay. It is very important to calculate energy efficiency and data transmission rate in wireless sensor networks because it is widely used in every field of life, especially when we are talking about medical, military and navigation system. After identifying main issues, this research will focus on energy efficiency and delay reduction. But other factors like security and average transmission time is not fully focused.

  • Movie Recommender System using Machine Learning

    Appears in:
    ct 22(3): e3

    Authors:
    Sonika Malik

    Published:
    11th Oct 2022

    Abstract:
    In this research, we propose a movie recommender system that can recommend movies to both new and existing customers. It searches movie databases for all of the relevant data, such as popularity and beauty that is required for a recommendation. We apply both content-based and collaborative filtering and evaluate their advantages and disadvantages. To build a system that delivers more exact movie recommendations, we employ hybrid filtering, which is a combination of the outcomes of these two processes. The recommendation engines are also used for business purposes and to make strategies for organizations. Due to the growing demands of customers and user’s recommendation systems plays a huge role. These recommender systems also help us to utilize our time in the busy world by giving us more relevant searches. These systems are generally used with the movie’s websites or with many commercial applications and are of great use. This type of recommendation system can be also used for precise results. It will make movies suggestions more relevant as per the need of the users.

  • Integrating the Fairlight CVI into the video workflow

    Appears in:
    ct 22(3): e2

    Authors:
    D.J.E. Nunn

    Published:
    30th Aug 2022

    Abstract:
    The Fairlight Computer Video Instrument (CVI) is one of the earliest video synthesisers, released in 1984. Over time the aesthetic of its effects has evolved from revolutionary to retro. Although MIDI was developed at around the same time, the CVI is controllable via RS232 rather than MIDI. This paper reviews its history and applications in live and studio-based video production environments. A method is outlined for controlling the CVI that allows sequencing of control data, effect automation, and integration with a digital audio workstation. Results are presented from a system using Logic Pro X for sequencing and Processing for MIDI-serial conversion.

  • Quadcopter Vehicle Proportional-Integral-Derivative Controller (PIDC) Tuning by Particle-Swarm Optimization (PSO)

    Appears in:
    ct 22(31): e5

    Authors:
    Abdullah Al Gizi

    Published:
    16th Aug 2022

    Abstract:
    Inspection of the faults and damages in high voltage transmission lines is not only unsafe and costly but also a very time-consuming process. In addition, it demands highly skilled manpower for the operation at tens of meters above the ground on cables carrying thousands of Volts. Meanwhile, the Quadcopter Aerial Vehicle (QAV) system became a popular alternative for aerial photography applications due to its low cost, ease of usage, and fast response wherein the proportional-integral-derivative controller (PIDC) is used. The PID controller compares the expected location of the drone with the actual measured position thereby can accurately detect the faults in the transmission lines. Based on these factors, in this study, the flight simulation is done according to the desired flight path, and drone imagery is used for (insulator, power line, and porcelain) flaw identification. Furthermore, three movements (roll, pitch, and yaw) of the quadcopter were controlled by different PIDC that were optimized using the particle swarm optimization (PSO). The MATLAB/Simulink application was used to develop the system and simulate the results (R2021b). This clearly suggested that the quadcopter continues to fly on a trajectory with minimum inaccuracy, wherein the PIDC operated as a closed-loop adaptive controller. Finally, the PSO-PIDC outperformed the PIDC due to the critical nature of manual gain modification for quadcopter flight stability.

  • TailorEd: Classroom Configuration and Activity Identifiers (CCID & CAID)

    Appears in:
    ct 22(3): e1

    Authors:
    Navid Shaghaghi, Kristin Lee, Julia Voss, Quan Nguyen, Andres Calle

    Published:
    28th Jul 2022

    Abstract:
    INTRODUCTION: The study of how classroom layout and activities affect learning outcomes of students with different demographics is difficult because it is hard to gather accurate information on the minute by minute progression of every class in a course. Furthermore, the process of data gathering must produce an abundance of data to work with and hence must be automated. OBJECTIVES: A machine learning model trained on images of a classroom and thus capable of accurately labeling the classroom layout and activity of many thousands of images much faster and cheaper than employing a human.  METHODS: Transfer learning can allow for preexisting computer vision models to be retrained on a smaller, more specific dataset in order to still achieve a highly accurate result.  RESULTS: In the case of the classroom layout, the final model achieved an accuracy of 97% on a four category classification. And for detecting the classroom activity, after experimentation with several different versions that could work on a very small sample sizes, the best model achieved an accuracy of 86.17%. CONCLUSION: In addition to showing that using computer vision to determine human activities is possible albeit more difficult than layouts of inanimate objects such as classroom desks, the study shows the differences between the use of self-supervised learning techniques and data augmentation techniques in order to overcome the problem of small training data-sets.

  • Capturing Racial & Gender Inequities on Social Media Platforms using Machine Learning

    Appears in:
    ct 22(31): e4

    Authors:
    Harshita Chopra, Aniket Vashishtha, Sonika Malik

    Published:
    6th Jul 2022

    Abstract:
    Online social media platforms provide a continuously evolving database due to the highly increasing popularity and rapid expansion of its user base. Users share their life experiences towards various inequity incidents faced at the workplace on the basis of their race or gender on these platforms while maintaining their anonymity. We aim at utilising famous social media platforms to perform extensive analysis and classification tasks for posts capturing instances of various types of Inequalities prevalent in today’s workplace. We present a framework to mine opinions expressed towards sexual harassment, mental health, racial injustice and gender-based bias in the corporate workplace using NLP techniques on social media data. The documents are represented by semantic similarity to aspect embedding’s captured using an attention-based framework for aspect extraction. In addition, we used scores from Empath categories to add information related to emotional facets.

  • Methodology to eliminate errors in machining processes through Augmented Reality Applications

    Appears in:
    ct 22(31): e3

    Authors:
    Manuel MERAZ MÉNDEZ, Elva Lilia REYNOSO JARDON

    Published:
    6th Jul 2022

    Abstract:
    Today, precision machining companies must implement new technologies to meet the requirements of the aerospace and automotive industries to maintain their competitiveness in the market and create new business opportunities. It has currently been observed that machining companies face errors in their processes that affect the quality of the products, the operation of the process, the useful life of the machines, and the tools. This research project aims to develop a methodology to reduce errors in Computerized Numerical Control machining (CNC) processes with Augmented Reality Applications (AR-Apps) that help operators interpret manufacturing drawings and assembly operations optimize Setup operations and ensure the reliability of the machining. It begins with a questionnaire applied to a sample of machining companies from Chihuahua Mexico City. To identify the factors that generate critical errors in the machining processes. The main results obtained in this paper are reduction of downtime, elimination of scrap, increment cutting tools life, optimize the machining process, increase productivity, and improved product quality. AR -apps implementation offers a low-cost alternative solution that operators and technicians can use very easily because it is a powerful tool that helps work more efficiently through virtual environments, reducing errors and optimizing the process of machining.

  • Using Blockchain to Ensure the Integrity of Digital Forensic Evidence in an IoT Environment

    Appears in:
    ct 22(31): e2

    Authors:
    Muhammad Shoaib Akhtar, Tao Feng

    Published:
    3rd Jun 2022

    Abstract:
    Digital forensics deals with digital evidence. Digital forensics is the study of data detection, acquisition, processing, analysis, and reporting. Encouraging the use of digital forensics in law enforcement investigations. With digital forensics, you can find out what data was taken and how it was copied or spread. Some hackers purposefully destroy data to harm their targets. In other cases, malicious software or hacker involvement can accidentally corrupt vital data. Digital forensics faces challenges of security and integrity. IoT devices can collect digital forensic evidence in an IoT setting, putting cybercrime agencies at danger owing to security and integrity. Many studies have been done recently to improve IoT based digital forensics integrity and security, but researchers face the risk of confidentiality. Recent research shows that digital forensics still faces manipulation and security issues. So a clever and effective approach is needed that not only protects security and integrity but also anticipates threats. So we propose an intelligent and effective solution based on Blockchain and Hashing algorithms. We will store the data collected from IoT devices into Blockchain. Anomalies in the evidence and transactions will be predicted using Machine Learning boosted models. So the proposed model works well because it can predict attacks early on.

  • IoT Based Detection of Molded Bread and Expiry Prediction using Machine Learning Techniques

    Appears in:
    ct 22(31): e1

    Authors:
    Muhammad Shoaib Akhtar, Tao Feng

    Published:
    27th Apr 2022

    Abstract:
    Expiration of a bread is a very popular issue in food logistics. Due to various conditions fungal bread can cause food poisoning for consumers. As a result, nausea, diarrhea and different medical issues appear in people. For this purpose, an intelligent system required for the detection of present condition of bread is required which will help the stores and consumers. In this study, we have developed a prototype made up of Arduino Nano as a microcontroller, MQ series sensors for CO and CO2 detection in shopper bags of bread in order to collect data. This data is further processed in different machine learning algorithms for the detection of current condition of bread in these stores. The data collected from these sensors was imbalanced. Data collected from sensors is then balanced by using SMOTE and TOMEC Links (data balancing techniques). Furthermore, data preprocessing and feature engineering has been applied on IoT Based dataset to improve its efficiency. We have applied linear learning models for the prediction of current condition of bread. Within linear models, Gaussian Naïve Bayes has scored highest accuracy of 81.54%.

  • Smart Attendance Management System Using Face Recognition

    Appears in:
    ct 18(17): e4

    Authors:
    Faheem Yar Khuhawar, Kaneez Laila Bhatti, Sheeraz Ahmed Memon, Laraib Mughal

    Downloads:
    37585

    Abstract:
    To maintain the attendance record with day to day activities is a challenging task. The conventional method of calling name of each student is time consuming and there is always a chance of proxy attendance. The following system is based on face recognition to maintain the attendance record of students. The daily attendance of students is recorded subject wise which is stored already by the administrator. As the time for corresponding subject arrives the system automatically starts taking snaps and then apply face detection and recognition technique to the given image and the recognize students are marked as present and their attendance update with corresponding time and subject id. We have used deep learning techniques to develop this system, histogram of oriented gradient method is used to detect faces in images and deep learning method is used to compute and compare feature facial of students to recognize them. Our system is capable to identify multiple faces in real time.

  • Time-Series Prediction of Cryptocurrency Market using Machine Learning Techniques

    Appears in:
    ct 21(28): e4

    Authors:
    Ali Hassan, Muhammad Shuaib Iqbal, Fawwad Hassan Jaskani, Mahir Iqbal, Khurum Iqbal

    Downloads:
    9546

    Abstract:
    In the market of cryptocurrency the Bitcoins are the first currency which has gain the significant importance. To predict the market price and stability of Bitcoin in Crypto-market, a machine learning based time series analysis has been applied. Time-series analysis can predict the future ups and downs in the price of Bitcoin. For this purpose we have used ARIMA, FBProphet, XG Boosting for time series analysis as a machine learning techniques. The parameters on the basis of which we have evaluated these models are Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and R2. We conduct experiments on these three techniques but after conducting time series analysis, ARIMA considered as the best model for forecasting Bitcoin price in the crypto-market with RMSE score of 322.4 and MAE score of 227.3. Additionally, this research can be helpful for investors of crypto-market.

  • The future of Artificial Intelligence in Cybersecurity: A Comprehensive Survey

    Appears in:
    ct 21(28): e3

    Authors:
    Zhang Jiayuan, Feng Tao, Muhammad Shoaib Akhtar

    Downloads:
    8345

    Abstract:
    AI in Cybersecurity Market scheme helps organizations in observance, detecting, reporting, and countering cyber threats to keep up information confidentiality. The increasing awareness among folks, advancements in info technology, up-gradation of intelligence and police work solutions, and increasing volume of knowledge gathered from numerous sources have demanded the utilization of reliable and improved cybersecurity solutions all told industries. The increase in the incidence and quality of cyber-attacks is driving AI-enabled cyber systems. Increasing incidents of huge cyber-attacks globally have created awareness among organizations for securing their information. The motive behind these cyber-criminals are political competition, competitors move for gain and harming the name of others, international information theft, and radical non-secular cluster interest. Most cyber-attacks are for gain. In this review we have presented some previous studies related to Cybersecurity which involves AI.

  • The Significance of a Body in Contemporary Arts

    Appears in:
    ct 16(6): e2

    Authors:
    Artur Krukowski, Emmanouela Vogiatzaki

    Downloads:
    4585

    Abstract:
    This paper discusses the role and significance of a body in Performance Art. Considering that Art reflects social, cultural and sometimes political realities, we identify types of messages that an artwork using advanced technological might transmit to us, spectators or artists. This paper focusses on the Cyborg Theatre, whereby the technology is its inherent element without which the performance could not happen. Such a technological performance cannot occur without a body. We refer here to a cyborg body as a human organism extended with mechanical parts, which integrate non organic components in order to gain meaning within the artwork. By focusing on such a theatrical performance, we observe a relationship developing between the performer and the spectator. This is an unusual interaction, which deserves our attention. We claim that both the performer and the spectator take part in a social event that does not only represent societal realities, but also indicates future ones.

  • Indoor Navigation using Augmented Reality

    Appears in:
    ct 21(26): e1

    Authors:
    Jayakrishna V, John Cheriyan, Joel Sebastian, JJ Ganesh, Ashly Martin

    Downloads:
    3922

    Abstract:
    This paper introduces the idea of Indoor Navigation using Augmented Reality. With the increase in complex building structures, people of different age may find it difficult to navigate within such structures. This paper provides a solution for this trouble using available and accessible resources. Using this application, a shop within a shopping mall, a specific room in a hotel etc., can be easily located and the user is provided with reasonably accurate visual assistance through their smartphone to reach his preferred location. The proposed system is inspired by augmented reality and 2-D Visual markers are the fundamental elements used in this system. Multiple visual markers are placed within the complex building structure and on scanning these visual markers using the application, users are led to their destination using arrows displayed on the screen.The application allows the user to choose their preferred destination and also permits them to change their destination in between.

  • Emotional interactive movie: adjusting the scenario according to the emotional response of the viewer

    Appears in:
    ct 17(10): e1

    Authors:
    Romain Cohendet, Anne-Laure Gilet, Matthieu Perreira Da Silva, Patrick Le Callet

    Downloads:
    2905

    Abstract:
    Emotional interactive movie is a kind of film unfolding in different ways according to the emotion the viewer experiences. The movie is made of several sequences; their combination determines the particular scenario experienced. In this paper, we describe the system and its implementation by providing combination selection criteria. We measured neurophysiological and ocular activities of 60 individuals viewing an experimental interactive short-movie composed of 12 different scenarios. For this purpose, we combined an electroencephalography headset which directly provides emotional data with an eye-tracker in order to simultaneously investigate the position of viewer’s gaze. From the collected data analysis, we propose a functional version of the emotional interactive movie, which was used in a so called “emotional cinema” during public exhibitions.

  • A Review of Gamification in Virtual Reality (VR) Sport

    Appears in:
    ct 19(21): e3

    Authors:
    Azyan Yusra Kapi, Mohd Shahrizal Sunar, Nurshamine Nazira Nor

    Downloads:
    2858

    Abstract:
    PURPOSE: To identify the main findings from research on gamified virtual reality in sport METHODS: The digital databases for this review were searched and visited on 19 May 2019. Gamification AND (“virtual reality” OR sports fitness) were used as a search string or keyword in the paper selection. RESULTS: Thirty -three papers were found after the preliminary searches to narrow down the selections that align with the goals of this study. The selected papers were examined to investigate the characteristics of gamification in a broad context of sports. These findings suggest that the use of gamification methods help physical exercise in the immersive VR setting. CONCLUSION: Through the outcomes of user experience, it can prove that gamification components are boosting the pleasure of the user throughout the physical activity and provide a set of rules to encourage the athlete or user to perform better. Besides, generality of impacts with VR and gamification in sports has been discussed in this paper by listing the advantages and limitations. However, findings need more varied populations, particularly elements, athletes, kids, and older people.

  • An overview of the applications of Artificial Intelligence in Cybersecurity

    Appears in:
    ct 21(29): e4

    Authors:
    Tao Feng, Muhammad Shoaib Akhtar

    Downloads:
    2853

    Abstract:
    The rates at which cyber-attacks are performed have made the cybersecurity unprotected and make it impossible for the security experts to evaluate and combat every new type of cyber-attack. Today's digital age necessarily requires the protection of a vast amount of valuable electronic data from cyber-attacks. Cyber-attacks can destroy the reputation of organizations even shutdown organizations. The protection of cybersecurity is inevitable. In this paper, we have highlighted the potential applications of AI in cybersecurity. Artificial intelligence has advanced to the point where it has surpassed human performance in tasks like data analytics. This study was carried out using systematic literature review; the relevant literature was collected from google scholar, research gate, science direct, IEEE Xplore, Digital Library and Microsoft academic search engines and databases. Our study resulted that AI applications in cybersecurity have many advantages than disadvantages. AI-based applications of cybersecurity can improve the security of cyberspace. This is evidenced by the rising of AI engines in computer security rather than traditional scanning engines.

  • Digital Society and Economy for People with Disabilities in Industry 4.0 : Malaysia Perspectives

    Appears in:
    ct 19(20): e5

    Authors:
    Mohd Shahrizal Sunar, Ruzimi Mohamed, Ruhiyati Idayu Abu Talib

    Downloads:
    2826

    Abstract:
    One of the key trends driving revolution in Industry 4.0 is digital society and economy. In this paper, we argue that the advancement of technology in Industry 4.0, which covers growth areas such as big data and machine learning, cybersecurity, digital currencies, blockchain and the Internet of Things (IoT) with expected creations of new job opportunities in the areas of Cyber Security, Data Analytics, Network Infrastructure and Software Development that can easily be done at home, has produced an ideal scenario in the context of job opportunities for People with Disabilities (PWDs). Greater accessibility to education with help from assistive technology opens up a lot of opportunities for PWDs to enhance their knowledge in Industry 4.0.

  • Evaluation of a Facial Animation Authoring Pipeline Seamlessly Supporting Performance Capture and Manual Key-pose Editing

    Appears in:
    ct 15(3): e4

    Authors:
    Alexis Heloir, Fabrizio Nunnari

    Downloads:
    2755

    Abstract:
    In this paper, we present an architecture following a novel animation authoring pipeline seamlessly supporting performance capture and manual editing of key-frames animation. This pipeline allows novice users to record and author sophisticated facial animations in a fraction of the time that would be required using traditional animation tools. This approach paves the way towards novel animation pipelines which seamlessly merge the roles of the animator and the actor. The second contribution is a method assessing a facial retargeting system, we conducted a user study where participants assessed the emotions conveyed by the facial expression displayed in the control and the authored animation. Contrary to existing evaluation methods, it factors out possible misinterpretations of the intended emotion and focuses on assessing the retargeting quality.
Publisher
EAI
ISSN
2409-9708
Number of Volumes
9
Last Published
2022-07-12
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