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18th international conference on Interfaces and Human computer Interaction 2024, IHCI 2024, the 17th international conference on Game and Entertainment Technologies 2024, GET 2024 and the 18th international conference on computer graphics, Visualization, computer vision and Image Processing 2024, CGVCVIP 2024, Part of the 18th Multi conference on computer Science and Information Systems 2024, MCCSIS 2024

作者： Razak, Fatin Nasuha Abdul Kamsin, Amirrudin Rahman, Hameedur Faculty of Computer Science and Information Technology Universiti Malaya WP Kuala Lumpur Kuala Lumpur50603 Malaysia Faculty of Computing and AI Air University Islamabad44000 Pakistan

ISBN: (纸本)9789898704580

Games, particularly serious games (SGs), have long been embraced in education for their inherent engagement and motivational qualities, especially among younger learners. In the realm of STEM education, SGs have emerged as a technological strategy to enhance student engagement and performance. this paper addresses the growing interest in SG implementation for computational thinking (CT) development within STEM education. through the introducing of a Game Learning Analytics (GLA) framework, this research explores the predictive potential of technological tools in assessing learners' performance. Focused on the creation of SGs, the GLA framework aims to elucidate the relationship between SG participation and CT skill development. the study proposes a methodological approach for implementing GLA to predict STEM learners' performance in SGs, contributing to the ongoing discourse on leveraging technology to enhance education outcomes. © 2024 Interfaces and Human computer Interaction. All Rights Reserved.

关键词： Contrastive Learning

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EXPLORATORY STUDY ON QUANTIFYING COMPLEXITY IN thE TEMPORAL STRUCTURE OF ELECTROACOUSTIC MUSIC 18

EXPLORATORY STUDY ON QUANTIFYING COMPLEXITY IN THE TEMPORAL ...

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作者： Hayata, Jumpei Honda, Shingo Arai, Soma Ohmura, Hidefumi Shibayama, Takuro Tokyo Denki University Ishizuka Hatoyama Hiki Saitama362-0074 Japan Tokyo University of Science 2641 Yamazaki Chiba Noda278-0022 Japan Tokyo College of Music 1-9-1 Kamimeguro Tokyo Meguro153-0051 Japan

ISBN: (纸本)9789898704580

the music created by this study’s authors was electroacoustic, which is more complex than ordinary popular music. Individuals often consider highly complex music as being difficult to understand;however, this study’s social activities, in which individuals were encouraged to create their own electroacoustic music, indicated that all participants enjoyed it. this indicated that efforts in this social practice may be changing "difficult things" into "fun things." this process of extending "fun things" is useful for extending the concept of "entertainment" in Game and Entertainment Technology. therefore, this study aimed to verify that complexity in music increases in the order of "normal (8-beat, etc.) music, experimental popular music, electroacoustic music, and noise music." To test this hypothesis, this study attempted to compare the rhythmic structure of "normal music" and "experimental popular music." the results indicated that the rhythmic structure of the experimental popular music was more complex than that of normal popular music. Furthermore, it is strongly suggested that electroacoustic music, which has no rhythmic structure, has a more complex rhythmic structure. Furthermore, it can be stated that inexperienced individuals enjoyed the creation of "music" that has no clear rhythmic synchronization. this extended these individuals’ traditional concept of "entertainment", and can be further extended by deepening this activity in the future. © 2024 Interfaces and Human computer Interaction. All Rights Reserved.

关键词： Human computer interaction

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Deep Scene Synthesis of Atlanta-World Interiors from a Single Omnidirectional Image

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IEEE TRANSACTIONS ON VISUALIZATION AND computer graphics 2023年第11期29卷 4708-4718页

作者： Pintore, Giovanni Bettio, Fabio Agus, Marco Gobbetti, Enrico CRS4 Turin Italy HBKU Doha Qatar

We present a new data-driven approach for extracting geometric and structural information from a single spherical panorama of an interior scene, and for using this information to render the scene from novel points of view, enhancing 3D immersion in VR applications. the approach copes with the inherent ambiguities of single-image geometry estimation and novel view synthesis by focusing on the very common case of Atlanta-world interiors, bounded by horizontal floors and ceilings and vertical walls. Based on this prior, we introduce a novel end-to-end deep learning approach to jointly estimate the depth and the underlying room structure of the scene. the prior guides the design of the network and of novel domain-specific loss functions, shifting the major computational load on a training phase that exploits available large-scale synthetic panoramic imagery. An extremely lightweight network uses geometric and structural information to infer novel panoramic views from translated positions at interactive rates, from which perspective views matching head rotations are produced and upsampled to the display size. As a result, our method automatically produces new poses around the original camera at interactive rates, within a working area suitable for producing depth cues for VR applications, especially when using head-mounted displays connected to graphics servers. the extracted floor plan and 3D wall structure can also be used to support room exploration. the experimental results demonstrate that our method provides low-latency performance and improves over current state-of-the-art solutions in prediction accuracy on available commonly used indoor panoramic benchmarks.

关键词： Omnidirectional 360 immersive view AR/MR/VR for architecture computer vision Machine learning

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EV-LFV: Synthesizing Light Field Event Streams from an Event Camera and Multiple RGB Cameras

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IEEE TRANSACTIONS ON VISUALIZATION AND computer graphics 2023年第11期29卷 4546-4555页

作者： Lu, Zhicheng Chen, Xiaoming Chung, Vera Yuk Ying Cai, Weidong Shen, Yiran Beijing Technol & Business Univ Sch Comp Sci & Engn Beijing Peoples R China Univ Sydney Sch Comp Sci Sydney Australia Shandong Univ Sch Software Jinan Peoples R China

Light field videos captured in RGB frames (RGB-LFV) can provide users with a 6 degree-of-freedom immersive video experience by capturing dense multi-subview video. Despite its potential benefits, the processing of dense multi-subview video is extremely resource-intensive, which currently limits the frame rate of RGB-LFV (i.e., lower than 30 fps) and results in blurred frames when capturing fast motion. To address this issue, we propose leveraging event cameras, which provide high temporal resolution for capturing fast motion. However, the cost of current event camera models makes it prohibitive to use multiple event cameras for RGB-LFV platforms. therefore, we propose EV-LFV, an event synthesis framework that generates full multi-subview event-based RGB-LFV with only one event camera and multiple traditional RGB cameras. EV-LFV utilizes spatial-angular convolution, ConvLSTM, and Transformer to model RGB-LFV's angular features, temporal features, and long-range dependency, respectively, to effectively synthesize event streams for RGB-LFV. To train EV-LFV, we construct the first event-to-LFV dataset consisting of 200 RGB-LFV sequences with ground-truth event streams. Experimental results demonstrate that EV-LFV outperforms state-of-the-art event synthesis methods for generating event-based RGB-LFV, effectively alleviating motion blur in the reconstructed RGB-LFV.

关键词： Machine Learning computer vision Light Field Image Processing Event-based vision

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Teaching Methods For Sharing the Creation Of Electroacoustic Music With Inexperienced People 17

Teaching Methods For Sharing The Creation Of Electroacoustic...

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17th international conference on Interfaces and Human computer Interaction 2023, IHCI 2023, the 17th international conference on computer graphics, Visualization, computer vision and Image Processing 2023, CGVCVIP 2023 and 16th international conference on Game and Entertainment Technologies 2023, GET 2023

作者： Matsumoto, Miki Mashita, Takumi Arai, Soma Ohmura, Hidefumi Yaguchi, Hiroyuki Shibayama, Takuro Tokyo Denki University Ishizaka Hatoyama Hiki Saitama 350-0394 Japan Tokyo University of Science 2641 Yamazaki Noda Chiba278-0022 Japan Tokyo Collage of Music 1-9-1 Kamimeguro Meguro Tokyo153-0051 Japan

ISBN: (纸本)9789898704498

Our lab holds a workshop using computers to create electroacoustic music (EAM) for a variety of inexperienced people. Since EAM is positioned as an extension of contemporary music, which has a large philosophical component, it has not gained as many creators and listeners as popular music. the reason for this may be that, compared to music meant for entertainment, both the structure in music theory and the concepts in expressive practice create the impression among many people that EAMis difficult to understand. However, we observed that numerous people enjoy creating EAMin workshops. this may be because EAM is created not by following the rules of ordinary music theory, but by producing a montage of sound materials formed from fragments of recorded sounds along a computer timeline, allowing the listener to hear a near-perfect acoustic representation in real time through intuitive manipulation. through our creative method, we taught participants to capture their impressions of fragmented acoustic materials using metaphorical adjective pairs such as 'high-low' and 'hard-soft' and to maintain the intensity of the contrast between them. this study is based on an analysis of the works created in university courses that share the same teaching techniques as our workshops. the analytical procedure of the present study was as follows: (1) We selected an 'excellent' completed piece of music. (2) We individually extracted the acoustic materials that made up the piece. (3) We used pairwise comparison to examine the participants' impressions of all acoustic materials used in the given piece. (4) We carried out an analysis to determine whether the original piece maintained a high degree of contrast in the impression of the acoustic materials, thereby validating our instructional technique, which we empirically derived from past workshops. © 2023 Proceedings of the international conferences on Interfaces and Human computer Interaction 2023, IHCI 2023;computer graphics, Visualiza

关键词： computer games

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A Comprehensive Study on Image Matting Techniques for Alpha Estimation 10

A Comprehensive Study on Image Matting Techniques for Alpha ...

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17th INDIACom;2023 10th international conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Singh, Sweta Sharma, Dilip Kumar Gla University Department of Computer Engineering and Applications Mathura India

ISBN: (纸本)9789380544472

Natural Image Matting (NIM) possesses toughest challenge in the sector of computer graphics and computer vision. the problem is poorly presented when only input image is given, with no further information. Image matting is the technique of softly fetching a foreground object from the background in an image according to the definition provided by the matting equation. Based on their techniques of estimating alpha-matte, image matting methods can be broadly classified into Sampling based, Propagation based and Learning based matting methods. In this paper we have done a comprehensive analysis on various image matting methods along with their advantages, disadvantages and challenges. their mean square error (MSE) and sum of absolute differences (SAD) parameters are also analyzed. In this analysis we can conclude that Learning based methods outperforms other two methods. Among Learning based methods Cascade Picture Matting Network with Deformable Graph Refinement (Cas-DGR) and Tripartite Information Mining and Integration Network (TIMI-Net) approaches give better performance than other methods based on their MSE and SAD analysis. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Mean square error

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Building A Face Database Of Arab Faces Toward Evaluating Bias In Facial Analysis Systems 17

Building A Face Database Of Arab Faces Toward Evaluating Bia...

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作者： Khalil, Ashraf Glal, Suha Ahmed, Khider Khan, Sana Zeb Abdulgani, Aysha College of Technological Innovation Zayed University Abu Dhabi United Arab Emirates Mechatronics Engineering Graduate Program American university of Sharjah Sharjah United Arab Emirates Department of Computer Science and Engineering American university of Sharjah Sharjah United Arab Emirates United Arab Emirates University Al Ain United Arab Emirates

ISBN: (纸本)9789898704498

Machine learning algorithms are fundamentally driven by the data provided by humans;consequently, the decisions made by those algorithms are not free from human bias. this is particularly evident in the case of facial analysis systems that employ machine learning algorithms. Recent studies have shown that the decisions made by many of the commercially available facial analysis systems are prejudiced against certain groups of race, ethnicity, age, gender and culture. Further studies have identified that the underlying reason for such biased decisions is that the open source material available for facial image databases which are used in commerce and academia to train the algorithms has meager diversity in these categories. To compound this issue, facial analysis technology is promoted by influential companies and artificial intelligence service providers without affirming the fairness and accuracy of the decisions given by these systems. To minimize bias and ensure representation of the Middle Eastern population in the imminent growth of this technology, we propose the development of two Arab face databases along with an algorithmic audit involving seven commercially available facial analysis systems. Of the databases, the first, Arab-LEANA, will include 300 Arab subjects' face images with variation in lighting, expression, accessory, nationality and age (LEANA). the second, Arab Public Figures Faces (APFF), will contain images and videos of 300 Arab public figures captured "in the wild". Faces for APFF will be selected manually from the internet since manual selection of faces will result in a high degree of variability in scale, pose, expression, illumination, age, occlusion and make-up. these databases will provide the worldwide community of face recognition researchers with a large-scale, diverse collection of Arab face images for training and evaluating algorithms toward developing a more representative, and therefore more robust, capacity for facial analysis. T

关键词： Machine learning

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Spiking Convolutional vision Transformer

Spiking Convolutional Vision Transformer

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international conference on Semantic Computing

作者： Sameerah Talafha Banafsheh Rekabdar Christos Mousas Chinwe Ekenna Department of Computer Science Southren Illinois University IL USA Department of Computer Science Portland State University OR USA Department of Computer Graphics Technology Purdue University IN USA Department of Computer Science University at Albany NY USA

this paper introduces the design of a Spiking Convolutional vision Transformer (SCvT) by using the biological-inspired learning rules including spike-timing-dependent plasticity (STDP) and reward–modulated STDP (R-STDP) for a classification task. We describe the structure of the SCvT simulated with deep spiking convolutional neural networks (DSCNN) and give a detailed description of the classification strategy.

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Using Augmented Reality in Computing Higher Education 17th

Using Augmented Reality in Computing Higher Education

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17th international conference on Intelligent Tutoring Systems (ITS)

作者： Alshaikhi, Sarah Alshamrani Joy, Mike Princess Nourah Bint Abdulrahman Univ Dept Comp Sci Riyadh Saudi Arabia Univ Warwick Dept Comp Sci Coventry W Midlands England

ISBN: (纸本)9783030804213;9783030804206

In the past, the only way to receive educational content was through traditional methods, which included engaging the learners in full interaction with non-interactive books. Nowadays, we can generate three-dimensional virtual vision by using high-performance computer graphics, which is called Augmented Reality (AR). this research focuses on investigating a new approach to emerging and integrating computing education with AR technology in Saudi Arabia. the research will follow the design science methodology which is a mixed method approach for data collection and analysis. As design science research is considered to be problem focused research, its main tasks are the illustration of the design problems and evaluation of design solutions.

关键词： Augmented reality computer science Augmented reality in education

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A survey on the current state of the art on deep learning 3D reconstruction 17

A survey on the current state of the art on deep learning 3D...

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17th IEEE international conference on Intelligent computer Communication and Processing, ICCP 2021

作者： Maxim, Bogdan Nedevschi, Sergiu Technical University of Cluj-Napoca Computer Science Departament Cluj-Napoca Romania

ISBN: (纸本)9781665409766

Efficient 3D reconstruction from different kind of inputs is a long standing effort of computer vision. Recent advancements in the field of machine learning, specifically deep learning, have started an interest in studying how well these techniques apply to the 3D reconstruction problem. Current efforts employ two main research directions: techniques applied to a single object, trying to reconstruct the surface as closely as possible from different kind of inputs and techniques applied to scenes made from multiple objects, which deal with topological representations, color, illumination and resource consumption. With a plethora of applications in computer graphics and computer vision, the results given by the deep learning techniques start to gain a serious position in the field of 3D reconstruction, yet no survey exist on the recent advancements on these new techniques. this survey summarizes the recent trend and applications of the deep-learning 3D reconstruction methods. We focus on learnable reconstruction methods from inputs like single image, multi-image and point cloud, using different representations, such as voxels, meshes and signed distance fields. Starting by presenting the datasets used, we follow by showing the main deep learning methods using different representations, presenting advantages and disadvantages. the second half of this survey focuses on scene reconstructions and open problems. Finally we conclude with a discussion of the importance of the 3D reconstruction and its possible applications in different fields such as automotive and mixed reality. © 2021 IEEE.

关键词： Surveys

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