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18th International Conference on Tangible, Embedded, and Embodied interaction, TEI 2024

作者： Rallabandi, Vineetha Haynes, Alice C. Reed, Courtney N. Strohmeier, Paul Sensorimotor Interaction Max Planck Institute for Informatics Saarland Informatics Campus Saarbrücken Germany Human Computer Interaction Lab Saarland University Saarland Informatics Campus Saarbrücken Germany Biomedical Engineering and Imaging Sciences King's College London London United Kingdom

ISBN: (纸本)9798400704024

Fabrics are seen as the foundation for e-textile interfaces but contribute their own tactile properties to interaction. We examine the role of fabrics in gestural interaction from a novel, textile-focused view. We replicated an eTextile sensor and interface for rolling and pinching gestures on four different fabric swatches and invited 6 participants, including both designers and lay-users, to interact with them. Using a semi-structured interview, we examined their interaction with the materials and how they perceived movement and feedback from the textile sensor and a visual GUI. We analyzed participants' responses using a joint, reflexive thematic analysis and propose two key considerations for research in e-textile design: 1) Both sensor and fabric contribute their own, inseparable materiality and 2) Wearable sensing must be evaluated with respect to culturally situated bodies and orientation. Expanding on material-oriented design research, we proffer that the evaluation of eTextiles must also be material-led and cannot be decontextualized and must be grounded within a soma-aware and situated context. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Smart textiles

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Real-Time Facial Expression Recognition using Facial Landmarks and Neural Networks 12

Real-Time Facial Expression Recognition using Facial Landmar...

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12th Iranian/2nd International Conference on Machine vision and Image Processing, MVIP 2022

作者： Haghpanah, Mohammad A. Saeedizade, Ehsan Masouleh, Mehdi Tale Kalhor, Ahmad University of Tehran Human and Robot Interaction Lab School of Electrical and Computer Engineering Tehran Iran University of Nevada Department of Computer Science and Engineering Reno United States

ISBN: (纸本)9781665412162

This paper presents a lightweight algorithm for feature extraction, classification of seven different emotions, and facial expression recognition in a real-time manner based on static images of the human face. In this regard, a Multi-Layer Perceptron (MLP) neural network is trained based on the foregoing algorithm. In order to classify human faces, first, some pre-processing is applied to the input image, which can localize and cut out faces from it. In the next step, a facial landmark detection library is used, which can detect the landmarks of each face. Then, the human face is split into upper and lower faces, which enables the extraction of the desired features from each part. In the proposed model, both geometric and texture-based feature types are taken into account. After the feature extraction phase, a normalized vector of features is created. A 3-layer MLP is trained using these feature vectors, leading to 96% accuracy on the test set. © 2022 IEEE.

关键词： Emotion Recognition

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Scene Understanding in Pick-and-Place Tasks: Analyzing Transformations Between Initial and Final Scenes

Scene Understanding in Pick-and-Place Tasks: Analyzing Trans...

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Iranian Conference on Electrical Engineering (ICEE)

作者： Seraj Ghasemi Hamed Hosseini MohammadHossein Koosheshi Mehdi Tale Masouleh Ahmad Kalhor Human and Robot Interaction Lab School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (数字)9798350376340

ISBN: (纸本)9798350376357

With robots increasingly collaborating with humans in everyday tasks, it is important to take steps toward robotic systems capable of understanding the environment. This work focuses on scene understanding to detect pick-and-place tasks given initial and final images from the scene. To this end, a dataset is collected for object detection and pick-and-place task detection. A YOLOv5 network is subsequently trained to detect the objects in the initial and final scenes. Given the detected objects and their bounding boxes, two methods are proposed to detect the pick-and-place tasks which transform the initial scene into the final scene. A geometric method is proposed which tracks objects' movements in the two scenes and works based on the intersection of the bounding boxes which moved within scenes. Contrarily, the CNN-based method utilizes a Convolutional Neural Network to classify objects with intersected bounding boxes into 5 classes, showing the spatial relationship between the involved objects. The performed pick-and-place tasks are then derived from analyzing the experiments with both scenes. Results show that CNN-based method, by VGG-16 backbone, outscores the geometric method by roughly 12% in certain scenarios, with an overall success rate of 84.3%.

关键词： YOLO Electrical engineering Accuracy Tracking Transforms Feature extraction Manipulators

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Scene Understanding in Pick-and-Place Tasks: Analyzing Transformations Between Initial and Final Scenes

arXiv

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arXiv 2024年

作者： Ghasemi, Seraj Hosseini, Hamed Koosheshi, MohammadHossein Masouleh, Mehdi Tale Kalhor, Ahmad Human and Robot Interaction Lab School of Electrical and Computer Engineering University of Tehran Tehran Iran

With robots increasingly collaborating with humans in everyday tasks, it is important to take steps toward robotic systems capable of understanding the environment. This work focuses on scene understanding to detect pick-and-place tasks given initial and final images from the scene. To this end, a dataset is collected for object detection and pick-and-place task detection. A YOLOv5 network is subsequently trained to detect the objects in the initial and final scenes. Given the detected objects and their bounding boxes, two methods are proposed to detect the pick-and-place tasks which transform the initial scene into the final scene. A geometric method is proposed which tracks objects’ movements in the two scenes and works based on the intersection of the bounding boxes which moved within scenes. Contrarily, the CNN-based method utilizes a Convolutional Neural Network to classify objects with intersected bounding boxes into 5 classes, showing the spatial relationship between the involved objects. The performed pick-and-place tasks are then derived from analyzing the experiments with both scenes. Results show that CNN-based method, by VGG-16 backbone, outscores the geometric method by roughly 12% in certain scenarios, with an overall success rate of 84.3%.MSC Codes computer vision and Pattern Recognition (***), Systems and Control (***) © 2024, CC BY.

关键词： Convolutional neural networks

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Personalization Trade-offs in Designing a Dialogue-based Information System for Support-Seeking of Sexual Violence Survivors 22

Personalization Trade-offs in Designing a Dialogue-based Inf...

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2022 CHI Conference on human Factors in Computing Systems, CHI 2022

作者： Kim, Hyeok Hwang, Youjin Lee, Jieun Kwon, Youngjin Park, Yujin Lee, Joonhwan Computer Science Northwestern University EvanstonIL United States Human-Computer Interaction+Design Lab. Seoul National University Seoul Korea Republic of

ISBN: (纸本)9781450391573

The lack of reliable, personalized information often complicates sexual violence survivors' support-seeking. Recently, there is an emerging approach to conversational information systems for support-seeking of sexual violence survivors, featuring personalization with wide availability and anonymity. However, a single best solution might not exist as sexual violence survivors have different needs and purposes in seeking support channels. To better envision conversational support-seeking systems for sexual violence survivors, we explore personalization trade-offs in designing such information systems. We implement a high-fidelity prototype dialogue-based information system through four design workshop sessions with three professional caregivers and interviewed with four self-identified survivors using our prototype. We then identify two forms of personalization trade-offs for conversational support-seeking systems: (1) specificity and sensitivity in understanding users and (2) relevancy and inclusiveness in providing information. To handle these trade-offs, we propose a reversed approach that starts from designing information and inclusive tailoring that considers unspecified needs, respectively. © 2022 ACM.

关键词： Information systems

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DRDM: A Disentangled Representations Diffusion Model for Synthesizing Realistic Person Images

DRDM: A Disentangled Representations Diffusion Model for Syn...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Huang, Enbo Zhang, Yuan Huang, Faliang Zhang, Guangyu Liu, Yang Guangxi Key Lab of Human-machine Interaction and Intelligent Decision Nanning Normal University Nanning China School of Computer and Information Engineering Nanning Normal University Nanning China College of Mathematics and Informatics South China Agricultural University Guangzhou China School of Computer Science and Engineering Sun Yat-sen University Guangzhou China

ISBN: (纸本)9798350368741

Person image synthesis with controllable body poses and appearances is an essential task owing to the practical needs in the context of virtual try-on, image editing and video production. However, existing methods face significant challenges with details missing, limbs distortion and the garment style deviation. To address these issues, we propose a Disentangled Representations Diffusion Model (DRDM) to generate photo-realistic images from source portraits in specific desired poses and appearances. First, a pose encoder is responsible for encoding pose features into a high-dimensional space to guide the generation of person images. Second, a body-part subspace decoupling block (BSDB) disentangles features from the different body parts of a source figure and feeds them to the various layers of the noise prediction block, thereby supplying the network with rich disentangled features for generating a realistic target image. Moreover, during inference, we develop a parsing map-based disentangled classifier-free guided sampling method, which amplifies the conditional signals of texture and pose. Extensive experimental results on the Deepfashion dataset demonstrate the effectiveness of our approach in achieving pose transfer and appearance control. The associated project can be found at https://***/lovemusiceb/DRDM. © 2025 IEEE.

关键词： Diffusion Model Disentangled Representation human Parsing Person image synthesis

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Focus Cat: Designing Idle Games to Promote Intermittent Practice and On-Going Adherence of Breathing Exercise for ADHD 22

Focus Cat: Designing Idle Games to Promote Intermittent Prac...

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9th ACM SIGCHI Annual Symposium on computer-human interaction in Play, CHI PLAY 2022

作者： Sadprasid, Book Tabor, Aaron Scheme, Erik Bateman, Scott Faculty Of Computer Science University Of New Brunswick Canada Human Computer Interaction Lab University Of New Brunswick Canada Institute Of Biomedical Engineering University Of New Brunswick Canada

ISBN: (纸本)9781450392112

Adherence and frequency of play are well-established challenges for serious games that target breathing exercises, because exercises are most effective when practiced in short and frequent sessions. Researchers have recognized that elements of idle games ideally align with many therapeutic use cases because idle games have a frequently repeating gameplay cycle that draws people in for short play sessions. However, there is little research about how idle games can be used to motivate consistent, frequent practice of therapies like breathing exercises that are often recommended for chronic conditions like ADHD. This paper describes the design and implementation of a therapeutic idle game, Focus Cat. This game is designed to help people with ADHD incorporate breathing exercises into their symptom management routine. Our work demonstrates how the unique qualities of idle game design - including short, frequent gameplay sessions, simple mechanics that make mundane tasks engaging and mechanics that pull and push players into and out of active gameplay - can be used for ADHD breathing exercises to improve adherence and frequency of practice. © 2022 Owner/Author.

关键词： Game design

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“I can run at night!": Using Augmented Reality to Support Nighttime Guided Running for Low-vision Runners 25

“I can run at night!": Using Augmented Reality to Support N...

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Proceedings of the 2025 CHI Conference on human Factors in Computing Systems

作者： Yuki Abe Keisuke Matsushima Kotaro Hara Daisuke Sakamoto Tetsuo Ono Human-Computer Interaction Lab Hokkaido University Sapporo Hokkaido Japan School of Computing and Information Systems Singapore Management University Singapore Singapore Human-Computer Interaction Lab Hokkaido University Sapporo Hokkaido Japan and Kyoto Tachibana University Kyoto Japan

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Immediate effects of short-duration wellbeing practices on children’s handwriting and posture guided by a social robot

Immediate effects of short-duration wellbeing practices on c...

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IEEE International Workshop on Robot and human Communication (ROMAN)

作者： Daniel Carnieto Tozadore Melike Cezayirlioglu Chenyang Wang Barbara Bruno Pierre Dillenbourg Computer-Human Interaction in Learning and Instruction (CHILI) Lab EPFL Lausanne Switzerland

Handwriting practising, as any other repetitive task, often leads the practiser to an overconcentration state where their performance might be affected by postural and mental fatigue. Short breaks to perform unrelated activities, especially relaxation exercises, have shown to be a simple alternative to soften or postpone this phenomenon. Therefore, in this paper we are investigating the immediate effects of different types of short-duration relaxation exercises in the handwriting and posture of children aged from 8 to 10 in handwriting training. We divided 40 children in two groups performing the sessions, guided by a social robot, with small exercises of mindfulness or stretching in the middle of their training. Additionally, we analysed participants’ perceptions towards the robot leading these interactions. Results showed improvements in participants’ handwriting quality and posture maintenance regardless of the condition. Additionally, more positive feedback about the pause was reported from individuals in the mindfulness condition.

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RealityGit: Cross Reality Version Control of R&D Optical Workbench

RealityGit: Cross Reality Version Control of R&D Optical Wor...

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IEEE International Symposium on Mixed and Augmented Reality Workshops (ISMARW)

作者： Ke Li Tim Rolff Reinhard Bacher Frank Steinicke Deutsches Elektronen-Synchrotron DESY Germany Department of Informatics Human-Computer Interaction Universität Hamburg Department of Informatics Computer Vision Universität Hamburg

Multi-user collaboration at research and development (R&D) workbenches in advanced optics laboratories involves updating and documenting the status of hundreds of components. Although there are abundant mixed reality (MR) systems to support the collaboration of spatially co-located users, limited methods are available to facilitate cooperation in the spatial-temporal domain. Inspired by the version control workflow used in software development, we propose RealityGit, a novel cross-reality (CR) system design that leverages the recent advancements of neural radiance fields (NeRF). We illustrate how the NeRF model can be used to channel users with different extended reality (XR) experiences by providing an accurate immersive visual documentation of the historical states of a complex R&D workbench. We demonstrate the feasibility of such a system through an implementation where users could contribute to the version control workflows by integrating historical NeRF scans into their MR devices or providing status reviews by annotating or editing a NeRF model in virtual reality (VR).

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