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Researcher profile

Yoichi Ochiai

Yoichi Ochiai contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
Human-Computer InteractionArtificial IntelligenceComputer VisionGraphicseess.IVphysics.app-ph

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Published work

9 published item(s)

preprint2026arXiv

OnomaCompass: A Texture Exploration Interface that Shuttles between Words and Images

Humans can finely perceive material textures, yet articulating such somatic impressions in words is a cognitive bottleneck in design ideation. We present OnomaCompass, a web-based exploration system that links sound-symbolic onomatopoeia and visual texture representations to support early-stage material discovery. Instead of requiring users to craft precise prompts for generative AI, OnomaCompass provides two coordinated latent-space maps--one for texture images and one for onomatopoeic term--built from an authored dataset of invented onomatopoeia and corresponding textures generated via Stable Diffusion. Users can navigate both spaces, trigger cross-modal highlighting, curate findings in a gallery, and preview textures applied to objects via an image-editing model. The system also supports video interpolation between selected textures and re-embedding of extracted frames to form an emergent exploration loop. We conducted a within-subjects study with 11 participants comparing OnomaCompass to a prompt-based image-generation workflow using Gemini 2.5 Flash Image (&#34;Nano Banana&#34;). OnomaCompass significantly reduced workload (NASA-TLX overall, mental demand, effort, and frustration; p < .05) and increased hedonic user experience (UEQ), while usability (SUS) favored the baseline. Qualitative findings indicate that OnomaCompass helps users externalize vague sensory expectations and promotes serendipitous discovery, but also reveals interaction challenges in spatial navigation. Overall, leveraging sound symbolism as a lightweight cue offers a complementary approach to Kansei-driven material ideation beyond prompt-centric generation.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Reversible vertical positioning of acoustically levitated particle using a spiral reflector

Dynamic positioning in acoustic levitation typically depends on active control of the transducers phases, which necessitates complex driving electronics. While mechanically actuated reflectors offer a simpler alternative, achieving reversible transport along the vertical axis solely through mechanical actuation remains challenging. Here, we demonstrate vertical particle translation using a rotating spiral reflector with a half-wavelength pitch. With the rotation axis laterally offset relative to the acoustic focus, the spiral surface functions as a series of translating slopes. Experimental and numerical results confirm stable, bidirectional transport, yielding a vertical displacement of approximately $0.58λ$ per revolution and a maximum height of $3.18λ$, with radial confinement maintained within $0.24λ$. This approach provides a cost-effective solution for non-contact sample handling without active phase control.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

WhiteTesseract: Reframing the Interpretation of Cultural Heritage through XR and Conversational AI

Cultural heritage exhibitions often struggle to sustain attention and support reflective engagement. Physical exhibitions rely on fixed interpretive aids that lack adaptability to individual backgrounds or curiosity, and their effectiveness depends heavily on a visitor's Personal Context, prior knowledge, and cultural literacy. Meanwhile, digital exhibitions prioritize convenience and accessibility but risk weakening the Physical and Social Contexts that define embodied cultural experience. WhiteTesseract addresses this gap by enabling in-situ interpretation through high-resolution XR and conversational AI. The system integrates spatial intelligence via artwork recognition to allow visitors to selectively reduce environmental distractions (via diminished reality) and engage in context-aware dialogue (via large language models). The goal is to preserve the richness of the physical and social environment while providing a flexible space for personal reflection, enhancing Personal Context without compromising physical authenticity. We deployed the system in a Claude Monet exhibition and conducted a controlled user study with 26 participants. Quantitative results showed that WhiteTesseract modulation significantly increased average viewing duration from 35.3 to 98.3 seconds (p < 0.001). Analysis of 529 visitor-AI interactions revealed that 60% extended beyond factual queries to include analytical, emotional, and comparative inquiries. These findings demonstrate how XR and AI can enrich the physical exhibition experience by supporting deeper, more personalized engagement without displacing the embodied value of cultural heritage. We discuss technical and social constraints for real-world deployment and limitations of our controlled setting.

0 citations0 reviewsNo code linkedOpen access
preprint2024arXiv

Expanding Horizons in HCI Research Through LLM-Driven Qualitative Analysis

How would research be like if we still needed to &#34;send&#34; papers typed with a typewriter? Our life and research environment have continually evolved, often accompanied by controversial opinions about new methodologies. In this paper, we embrace this change by introducing a new approach to qualitative analysis in HCI using Large Language Models (LLMs). We detail a method that uses LLMs for qualitative data analysis and present a quantitative framework using SBART cosine similarity for performance evaluation. Our findings indicate that LLMs not only match the efficacy of traditional analysis methods but also offer unique insights. Through a novel dataset and benchmark, we explore LLMs&#39; characteristics in HCI research, suggesting potential avenues for further exploration and application in the field.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Deep Billboards towards Lossless Real2Sim in Virtual Reality

An aspirational goal for virtual reality (VR) is to bring in a rich diversity of real world objects losslessly. Existing VR applications often convert objects into explicit 3D models with meshes or point clouds, which allow fast interactive rendering but also severely limit its quality and the types of supported objects, fundamentally upper-bounding the &#34;realism&#34; of VR. Inspired by the classic &#34;billboards&#34; technique in gaming, we develop Deep Billboards that model 3D objects implicitly using neural networks, where only 2D image is rendered at a time based on the user&#39;s viewing direction. Our system, connecting a commercial VR headset with a server running neural rendering, allows real-time high-resolution simulation of detailed rigid objects, hairy objects, actuated dynamic objects and more in an interactive VR world, drastically narrowing the existing real-to-simulation (real2sim) gap. Additionally, we augment Deep Billboards with physical interaction capability, adapting classic billboards from screen-based games to immersive VR. At our pavilion, the visitors can use our off-the-shelf setup for quickly capturing their favorite objects, and within minutes, experience them in an immersive and interactive VR world with minimal loss of reality. Our project page: https://sites.google.com/view/deepbillboards/

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

See-Through Captions: Real-Time Captioning on Transparent Display for Deaf and Hard-of-Hearing People

Real-time captioning is a useful technique for deaf and hard-of-hearing (DHH) people to talk to hearing people. With the improvement in device performance and the accuracy of automatic speech recognition (ASR), real-time captioning is becoming an important tool for helping DHH people in their daily lives. To realize higher-quality communication and overcome the limitations of mobile and augmented-reality devices, real-time captioning that can be used comfortably while maintaining nonverbal communication and preventing incorrect recognition is required. Therefore, we propose a real-time captioning system that uses a transparent display. In this system, the captions are presented on both sides of the display to address the problem of incorrect ASR, and the highly transparent display makes it possible to see both the body language and the captions.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

A Preliminary Study for Identification of Additive Manufactured Objects with Transmitted Images

Additive manufacturing has the potential to become a standard method for manufacturing products, and product information is indispensable for the item distribution system. While most products are given barcodes to the exterior surfaces, research on embedding barcodes inside products is underway. This is because additive manufacturing makes it possible to carry out manufacturing and information adding at the same time, and embedding information inside does not impair the exterior appearance of the product. However, products that have not been embedded information can not be identified, and embedded information can not be rewritten later. In this study, we have developed a product identification system that does not require embedding barcodes inside. This system uses a transmission image of the product which contains information of each product such as different inner support structures and manufacturing errors. We have shown through experiments that if datasets of transmission images are available, objects can be identified with an accuracy of over 90%. This result suggests that our approach can be useful for identifying objects without embedded information.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Discussion of Intelligent Electric Wheelchairs for Caregivers and Care Recipients

In order to reduce the burden on caregivers, we developed an intelligent electric wheelchair. We held workshops with caregivers, asked then regarding the problems in caregiving, and developed problem-solving methods. In the workshop, caregivers&#39; physical fitness and psychology of the older adults were found to be problems and a solution was proposed. We implemented a cooperative operation function for multiple electric wheelchairs based on the workshop and demonstrated it at a nursing home. By listening to older adults, we obtained feedback on the automatic driving electric wheelchair. From the results of this study, we discovered the issues and solutions to be applied to the intelligent electric wheelchair.

0 citations0 reviewsNo code linkedOpen access