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Computer Vision Methods for Enhancin...
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Yu, Rui.
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Computer Vision Methods for Enhancing Remote Sighted Assistance.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Computer Vision Methods for Enhancing Remote Sighted Assistance./
作者:
Yu, Rui.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2023,
面頁冊數:
177 p.
附註:
Source: Dissertations Abstracts International, Volume: 85-05, Section: B.
Contained By:
Dissertations Abstracts International85-05B.
標題:
Visualization. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30720551
ISBN:
9798380730495
Computer Vision Methods for Enhancing Remote Sighted Assistance.
Yu, Rui.
Computer Vision Methods for Enhancing Remote Sighted Assistance.
- Ann Arbor : ProQuest Dissertations & Theses, 2023 - 177 p.
Source: Dissertations Abstracts International, Volume: 85-05, Section: B.
Thesis (Ph.D.)--The Pennsylvania State University, 2023.
Remote sighted assistance (RSA) has emerged as a conversational assistive technology for people with visual impairments (PVI), where a remote sighted agent interprets the real-time video feed coming from a visually impaired user's smartphone camera while conversing with the user to provide assistance. Due to its significant benefits for PVI, the RSA technology has attracted increasing attention from both academia and industry.With the growing complexity of tasks, researchers have found that reliance on smartphones' camera feed can be a limiting factor and reported several challenges for the agents, e.g., unfamiliarity with PVI's physical surroundings, difficulty in tracking moving objects, and interpreting various information in real-time. Since these challenges are related to understanding 3D environments and semantics from the live video, they can be potentially addressed by computer vision (CV) technologies. This dissertation aims to develop CV methods to enhance RSA services. The study has been carried out in three phases.In the first phase, we conducted a literature review and interviewed twelve RSA users to thoroughly understand the challenges in RSA. We summarized a comprehensive list of challenges, analyzed the causes and the technological needs, and thus identified some major CV problems in RSA. The second phase of the study is developing new methods to address key issues in the identified CV problems. In particular, we focus on addressing four representative CV problems: predicting the trajectories of pedestrians, recognizing persons or objects from camera feed, expanding the field of view of camera feed, and estimating the scale and depth in dual camera feed. The third phase is developing user-friendly RSA prototypes and verifying the CV methods through user studies. In our study, we focus on the exemplar problem of 3D indoor mapping and real-time localization. Specifically, we created an RSA prototype with ARKit-based iOS app for the third-phase study. Localizing RSA users on 3D maps in real-time has been proved effective for enhancing RSA services in our study. Through the three-phase study, we identified the challenges and CV problems in RSA, developed new methods for representative CV problems, and verified the effectiveness of exemplar CV techniques for supporting RSA.
ISBN: 9798380730495Subjects--Topical Terms:
586179
Visualization.
Subjects--Index Terms:
Remote sighted assistance
Computer Vision Methods for Enhancing Remote Sighted Assistance.
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Remote sighted assistance (RSA) has emerged as a conversational assistive technology for people with visual impairments (PVI), where a remote sighted agent interprets the real-time video feed coming from a visually impaired user's smartphone camera while conversing with the user to provide assistance. Due to its significant benefits for PVI, the RSA technology has attracted increasing attention from both academia and industry.With the growing complexity of tasks, researchers have found that reliance on smartphones' camera feed can be a limiting factor and reported several challenges for the agents, e.g., unfamiliarity with PVI's physical surroundings, difficulty in tracking moving objects, and interpreting various information in real-time. Since these challenges are related to understanding 3D environments and semantics from the live video, they can be potentially addressed by computer vision (CV) technologies. This dissertation aims to develop CV methods to enhance RSA services. The study has been carried out in three phases.In the first phase, we conducted a literature review and interviewed twelve RSA users to thoroughly understand the challenges in RSA. We summarized a comprehensive list of challenges, analyzed the causes and the technological needs, and thus identified some major CV problems in RSA. The second phase of the study is developing new methods to address key issues in the identified CV problems. In particular, we focus on addressing four representative CV problems: predicting the trajectories of pedestrians, recognizing persons or objects from camera feed, expanding the field of view of camera feed, and estimating the scale and depth in dual camera feed. The third phase is developing user-friendly RSA prototypes and verifying the CV methods through user studies. In our study, we focus on the exemplar problem of 3D indoor mapping and real-time localization. Specifically, we created an RSA prototype with ARKit-based iOS app for the third-phase study. Localizing RSA users on 3D maps in real-time has been proved effective for enhancing RSA services in our study. Through the three-phase study, we identified the challenges and CV problems in RSA, developed new methods for representative CV problems, and verified the effectiveness of exemplar CV techniques for supporting RSA.
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