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Multidimensional image morphing-fast image-based rendering of open 3D and VR environments

虚拟现实与智能硬件(中英文) 2025年第2期7卷 155-172页

作者： Simon SEIBT Bastian KUTH Bartosz von Rymon LIPINSKI Thomas CHANG Marc Erich LATOSCHIK Game Tech Laboratory Faculty of Computer ScienceNuremberg Institute of TechnologyNuremberg 90489Germany Department of Electrical Engineering and Computer Science Coburg University of Applied Sciences and ArtsCoburg 96450Germany Human-Computer Interaction Group Institute of Computer ScienceUniversity of WuerzburgWuerzburg 97074Germany

Background In recent years,the demand for interactive photorealistic three-dimensional(3D)environments has increased in various fields,including architecture,engineering,and ***,achieving a balance between the quality and efficiency of high-performance 3D applications and virtual reality(VR)remains *** This study addresses this issue by revisiting and extending view interpolation for image-based rendering(IBR),which enables the exploration of spacious open environments in 3D and ***,we introduce multimorphing,a novel rendering method based on the spatial data structure of 2D image patches,called the image *** this approach,novel views can be rendered with up to six degrees of freedom using only a sparse set of *** rendering process does not require 3D reconstruction of the geometry or per-pixel depth information,and all relevant data for the output are extracted from the local morphing cells of the image *** detection of parallax image regions during preprocessing reduces rendering artifacts by extrapolating image patches from adjacent cells in *** addition,a GPU-based solution was presented to resolve exposure inconsistencies within a dataset,enabling seamless transitions of brightness when moving between areas with varying light *** Experiments on multiple real-world and synthetic scenes demonstrate that the presented method achieves high"VR-compatible"frame rates,even on mid-range and legacy hardware,*** achieving adequate visual quality even for sparse datasets,it outperforms other IBR and current neural rendering *** Using the correspondence-based decomposition of input images into morphing cells of 2D image patches,multidimensional image morphing provides high-performance novel view generation,supporting open 3D and VR ***,the handling of morphing artifacts in the parallax image regions remains a topic for future resea

关键词： computer graphics 3D real-time rendering computer vision Image morphing Virtual reality

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A unified user behavior model for trajectory-based tasks with different types of path constraints

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science China(Information sciences) 2023年第10期66卷 316-318页

作者： Hao ZHANG Jin HUANG Huawei TU Feng TIAN Guozhong DAI Hongan WANG Beijing Key Laboratory of Human-Computer Interaction Institute of Software Chinese Academy of Sciences School of Computer Science and Technology University of Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Department of Computer Science and Information Technology La Trobe University

An important research branch of human-computer interaction(HCI) is to develop predictive models for human performance in fundamental interactions [1]. On today's graphical user interface(GUI), users often implicitly perform various trajectory-based interactions, such as navigating through menus [2], entering the boundary of a button,

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Pseudo-Haptics for Weight Perception in VR: Controller vs. Bare Hand interactions with Tracking Delay and Vertical Offset 10

Pseudo-Haptics for Weight Perception in VR: Controller vs. B...

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10th International Conference on Virtual Reality, ICVR 2024

作者： Hwang, Chiwoong Feuchtner, Tiare Gronbak, Kaj Aarhus University Department of Computer Science Denmark Konstanz University Human-Computer Interaction Group Germany

ISBN: (纸本)9798350364231

Training in virtual reality (VR) offers advantages such as a safe learning environment, good scalability, and cost saving. However, state-of-the-art simulations are limited in faithfully conveying real-world physical object properties such as weight without complex technologies and instrumentation of the user or environment, which may negatively impact learning. A potential solution is the application of pseudo-haptics: illusory haptic sensations induced by a mismatch between real and virtual hand positions. Researchers have proposed various pseudo-haptic techniques to alter the perception of weight in virtual environments, but their effectiveness with hand tracking compared to VR controllers is underexplored. Hence, we investigate impacts of the interaction method for two different types of pseudo-haptic feedback based on Tracking Delay and Vertical Offset. Our results indicate that pseudo-haptics can effectively facilitate the sensation of weight both with controllers and bare hands, whereby each has benefits: hand tracking can enhance body ownership, while controllers may improve perceived responsiveness of virtual environments. Also, pseudo-haptics with Tracking Delay may be preferable for repetitive lifting tasks, as Vertical Offset can be prone to higher physical demand. The current study provides insights into the design of pseudo-haptic feedback and interaction technologies for weight perception in VR. © 2024 IEEE.

关键词： Virtual environments

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A Reinforcement Learning Framework for Efficient Task Allocation among AGVs in Smart Warehouse

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IEEE Internet of Things Journal 2025年第11期12卷 16947-16961页

作者： Li, Shaofeng Zhao, Zejian Wang, Di Li, Ke Liu, Gang Wang, Quan Xidian University Key Laboratory of Smart Human-Computer Interaction and Wearable Technology of Shaanxi Province the School of Computer Science and Technology Xi'an710071 China Xidian University Guangzhou Institute of Technology Guangzhou510555 China

In smart warehouses that use automated guided vehicles (AGVs) for goods transportation, task allocation has a great impact on operational efficiency. Currently, warehouse task allocation is typically modeled as a pickup and delivery problem (PDP), which requires vehicles to start and return from the same depot to construct several closed-loop routes. This approach increases the vehicle travel distance without load in high-throughput warehouses and results in resource wastage. Thus we re-model the task allocation problem as an open-loop routing problem with heterogeneous starting points and name it capacitied multiagent open pickup and delivery problem (CMOPDP), which has more complex solution space and constraints than PDP. The solving speed of existing heuristic methods cannot meet the real-time processing demands of large-scale warehouses. And deep reinforcement learning (DRL)-based methods typically satisfy constraints through the output mask of decoders, which leads to unsatisfactory quality of solutions under complex constraints. To address these limitations, we design an DRL-based model with encoder-decoder architecture to solve the CMOPDP. Specifically, first, an encoder with heterogeneous attention is designed to fully explore constraint relationships between nodes. Second, we utilize dual decoders and information sharing to maximize vehicle-customer nodes matching. Finally, entropy rewards are introduced to enhance exploration during reinforcement learning, preventing the model from getting stuck in local optima. Extensive experiments on random datasets and various warehouse maps demonstrate that our method improves solution quality by at least 1.76% over baselines, while maintaining competitive solving time and exhibiting good generalization performance. © 2025 IEEE.

关键词： Deep reinforcement learning

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Exploring Multiscale Navigation of Homogeneous and Dense Objects with Progressive Refinement in Virtual Reality 32

Exploring Multiscale Navigation of Homogeneous and Dense Obj...

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32nd IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2025

作者： Pavanatto, Leonardo Giovannelli, Alexander Giera, Brian Bremer, Timo Miao, Haichao Bowman, Doug A. Virginia Tech Center for Human-Computer Interaction Department of Computer Science United States Lawrence Livermore National Laboratory Center for Applied Scientific Computing United States

ISBN: (纸本)9798331536459

Locating small features in a large, dense object in virtual reality (VR) poses a significant interaction challenge. While existing multiscale techniques support transitions between various levels of scale, they are not focused on handling dense, homogeneous objects with hidden features. We propose a novel approach that applies the concept of progressive refinement to VR navigation, enabling focused inspections. We conducted a user study where we varied two independent variables in our design, navigation style (STRUCTURED vs. UNSTRUCTURED) and display mode (SELECTION vs. EVERYTHING), to better understand their effects on efficiency and awareness during multiscale navigation. Our results showed that unstructured navigation can be faster than structured and that displaying only the selection can be faster than displaying the entire object. However, using an everything display mode can support better location awareness and object understanding. © 2025 IEEE.

关键词： Virtual reality

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BackTrace: A human-AI Collaborative Approach to Discovering Studio Backdrops in Historical Photographs 11th

BackTrace: A Human-AI Collaborative Approach to Discovering ...

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11th AAAI Conference on human Computation and Crowdsourcing, HCOMP 2023

作者： Lim, Jude Mohanty, Vikram Dodson, Terryl Luther, Kurt Center for Human-Computer Interaction and Department of Computer Science Virginia Tech United States

ISBN: (纸本)9781577358848

In historical photo research, the presence of painted backdrops have the potential to help identify subjects, photographers, locations, and events surrounding certain photographs. However, there are few dedicated tools or resources available to aid researchers in this largely manual task. In this paper, we propose BackTrace, a human-AI collaboration system that employs a three-step workfow to retrieve and organize historical photos with similar backdrops. BackTrace is a content-based image retrieval (CBIR) system powered by deep learning that allows for the iterative refnement of search results via user feedback. We evaluated BackTrace with mixed-methods evaluation and found that it successfully aided users in fnding photos with similar backdrops and grouping them into collections. Finally, we discuss how our fndings can be applied to other domains, as well as implications of deploying BackTrace as a crowdsourcing system. © 2023, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Photography

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A 2D Geometry Based Grasping Pose Generation Algorithm for a Two-Finger Robot Hand 31

A 2D Geometry Based Grasping Pose Generation Algorithm for a...

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31st International Conference on Electrical Engineering, ICEE 2023

作者： Akbari, Arash Akbari, Arman Masouleh, Mehdi Tale University of Tehran Department of Computer Science Tehran Iran School of Electrical and Computer Engineering Human and Robot Interaction Laboratory Tehran Iran

ISBN: (纸本)9798350312560

Robot grasping is of paramount importance in industrial and service robotics. In recent years, various data-driven algorithms have been proposed to solve the problem of grasp detection and a part of them are based on reinforcement learning (RL) approaches. In a variety of proposed algorithms, random key points are being employed which will make the learning process inefficient and time-consuming. In this paper, a geometry-based algorithm is presented which can find grasp poses based on the geometry of the unknown object and propose the ones which may lead to successful grasping. For the grasp contacts computation part, the presented algorithm produces a finite number of key points based on the 2D shape of the object from a specific point of view. Afterward, it will narrow down the candidate points and output a finite number of successful grasp poses based on three grasp quality metrics for various unknown objects. Three approaches are proposed in order to achieve center points which can describe different parts of a 2D shape. Then, the obtained points are used as the center of circles which are tangent to the 2D shape contour. Also, a new grasp quality metric is proposed. The time of the grasp and the amount of object disorientation after grasping are considered as a metric to evaluate the successfulness of the grasp. Simulation results demonstrate that the proposed algorithm for unknown object grasping can find a finite number of successful grasp poses for different seen or unseen objects without using any random point © 2023 IEEE.

关键词： Geometry

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Shift Aliasing Signal Data Augmentation Method for SSVEP-based BCIs 30

Shift Aliasing Signal Data Augmentation Method for SSVEP-bas...

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30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024

作者： Huang, Jiayang Wen, Hao Yang, Pengfei Yang, Keyi Xiong, Bang Xidian University School of Computer Science and Technology The Key Laboratory of Smart Human-Computer Interaction and Wearable Technology of Shaanxi Province Xi'an710126 China

ISBN: (纸本)9798350391916

The performance of training-based spatial filtering methods for steady-state visual evoked potential (SSVEP) decoding heavily relies on the availability of sufficient and high-quality calibration data. Limited calibration data can lead to suboptimal spatial filters and low signal-to-noise ratios in individual SSVEP templates, ultimately degrading the decoding accuracy and efficiency. To address this challenge, we propose a novel data augmentation method called Shift Aliasing Signal (SAS), which generates synthetic SSVEP epochs by estimating a mixing matrix from the available training data and applying time-shift operations while maintaining the essential features of SSVEP signals, such as their phase-locked nature and frequency-specific patterns. The SAS method introduces meaningful variations to enhance the training dataset. We integrate the SAS method with state-of-the-art training-based spatial filtering methods to create a powerful decoding framework for SSVEP-based brain-computer interface (BCI) systems. Extensive experiments on benchmark datasets demonstrate that the proposed SAS method significantly improves classification accuracy and information transfer rate, particularly in scenarios with limited calibration data, outperforming state-of-the-art training-based spatial filtering methods and other data augmentation techniques. © 2024 IEEE.

关键词： Signal to noise ratio

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CoLT: Enhancing Collaborative Literature Review Tasks with Synchronous and Asynchronous Awareness Across the Reality-Virtuality Continuum

CoLT: Enhancing Collaborative Literature Review Tasks with S...

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2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2023

作者： Tahmid, Ibrahim A. Rodrigues, Francielly Giovannelli, Alexander Lisle, Lee Thomas, Jerald Bowman, Doug A. Virginia Tech Center for Human-Computer Interaction Department of Computer Science BlacksburgVA United States

ISBN: (纸本)9798350328912

Collaboration plays a vital role in both academia and industry whenever we need to browse through a big amount of data to extract meaningful insights. These collaborations often involve people living far from each other, with different levels of access to technology. Effective cross-border collaborations require reliable telepresence systems that provide support for communication, cooperation, and understanding of contextual cues. In the context of collaborative academic writing, while immersive technologies offer novel ways to enhance collaboration and enable efficient information exchange in a shared workspace, traditional devices such as laptops still offer better readability for longer articles. We propose the design of a hybrid cross-reality cross-device networked system that allows the users to harness the advantages of both worlds. Our system allows users to import documents from their personal computers (PC) to an immersive headset, facilitating document sharing and simultaneous collaboration with both colocated colleagues and remote colleagues. Our system also enables a user to seamlessly transition between Virtual Reality, Augmented Reality, and the traditional PC environment, all within a shared workspace. We present the real-world scenario of a global academic team conducting a comprehensive literature review, demonstrating its potential for enhancing cross-reality hybrid collaboration and productivity. © 2023 IEEE.

关键词： Augmented reality

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Digital Shadows: Exploring the Other and the I in Communication with Thanabots 6

Digital Shadows: Exploring the Other and the I in Communicat...

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6th Social Robots with AI: Prospects, Risks, and Responsible Methods Robophilosophy, RP 2024

作者： Dobrosovestnova, Anna Machado, Felipe Reinboth, Tim Human Computer Interaction Group TU Wien Austria Department of Philosophy Cognitive Science Hub University of Vienna Austria

ISBN: (纸本)9781643685670

The development of large language models (LLMs) has led to the proliferation of chatbot services like ChatGPT, Replika and Project December further contributing to technologically mediated grief. Called variously griefbots, or thanabots, the postulated aim behind these technologies is to help people deal with the loss of their loved ones. Despite hype around these technologies in the media, little is still known about the actual mechanisms of how thanabots contribute to grieving. This paper contributes to answering this question by offering an interpretation of communication with thanabots through the prism of Yuri Lotman's autocommunication model. We start by examining how a thanabot can be framed as a communicational 'other'. Then we draw on phenomenology of grief literature to delineate the boundaries of such "otherness". In line with the Lotman's autocommunication model, we proceed to argue that conversing with a thanabot can be viewed as an instance of 'I-I' communication. Within this model, the bot functions as a secondary code that allows for new meaning to arise in the process of communication and, consequently, for a bereaved person to renegotiate their new identity in the face of loss. © 2025 IOS Press. All rights reserved.

关键词： I-I I-Other Large Language Models phenomenology of grief thanabots

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