Qingying Gao

🏫 Shanghai JianPing High school
🎓 CUFE BS Applied Stats & BEcon Finance
🎓 JHU MSE CS
🔛 JHU PhD CS

Low Vision Assistive Tool

2025

Walk, See, and Trace: A New Method for Object Labeling in Real-Life Settings

ARVO 2025

Qingying Gao Rama Chellappa Peng Cheng Kristen Shifflet Gordon E Legge Yingzi Xiong

KEYWORDS: Low Vision, Computer Vision, Assistive Tool

“What is in front of you?” Numerous studies attempt to understand the impact of low vision on object visibility using computer images, while real-life object visibility is underexplored despite greater ecological validity and critical perceptual factors such as binocular parallax and self-motion. We developed a “Walk, See, and Trace” task, in which observers wear light-weight glasses fitted with scene camera as they report and hand-trace the boundaries of objects in real environment. Here we report the initial evaluation in individuals with normal vision.

Measuring Critical Viewing Distance of Computer Vision Models in Hazard Recognition

ARVO 2025

Seungeon Han Clara Kim Qingying Gao Kristen Shifflet Rama Chellappa Peng Cheng Gordon E Legge Yingzi Xiong

KEYWORDS: Low Vision, Computer Vision, Model Assessment

As computer vision (CV) applications gain popularity in assisting blind and low-vision individuals, model evaluation should be tailored to these users’ practical needs. In a hazard warning context, it is critical that an assistive application can detect a hazard before the user reaches a contact range. We propose using critical viewing distance (CVD), a metric motivated by human vision evaluation, to assess CV models for hazard recognition. Here, we demonstrate how CVD changes across models, lighting conditions, and hazard types to prove the necessity of such a metric.

2024

Creating A “Visually Impaired” Character Recognition Model for Text Accessibility Assessment

ARVO 2024

Qingying Gao Roberto Manduchi Pradeep Y Ramulu Gordon E Legge Yingzi Xiong

KEYWORDS: Low Vision, Computer Vision

Low vision individuals use their residual vision in their daily life to read text such as price tags, street signs, medicine labels. However, there is no objective tool for evaluating text accessibility for low vision. … We aim to design a new framework combining OCR and human contrast sensitivity functions (CSF) to simulate the text recognition capability of low vision.

Grow AI like a Child

2024

Vision Language Models See What You Want but not What You See

2024

Qingying Gao Yijiang Li Haiyun Lyu Haoran Sun Dezhi Luo Hokin Deng

KEYWORDS: VLM, Cognitive development

Knowing others’ intentions and taking others’ perspectives are two core components of human intelligence that are typically considered to be instantiations of theory-of-mind. Infiltrating machines with these abilities is an important step towards building human-level artificial intelligence. … We find VLMs achieving high performance on intentionality understanding but lower performance on perspective-taking. This challenges the common belief in cognitive science literature that perspective-taking at the corresponding modality is necessary for intentionality understanding.

Augmented Reality

2023

Mixed Reality Guided Root Canal Therapy

AE-CAI Workshop 2023

Fangjie Li* Qingying Gao* Nengyu Wang Nicholas Greene Tianyu Song Omid Dianat Ehsan Azimi

* Co-first author

KEYWORDS: Mixed Reality, Root Canal Therapy, Navigation, Augmented Reality

Root Canal Therapy (RCT) is a widely performed procedure in dentistry, with over 25 million individuals undergoing it annually. This procedure is carried out to address inflammation or infection within the root canal system of affected teeth. However, accurately aligning CT scan information with the patient’s tooth has posed challenges, leading to errors in tool positioning and potential negative outcomes. To overcome these challenges, we have developed a mixed reality application using an Optical See-Through Head-Mounted Display (OST-HMD)…