How Blind People Interact with Visual Content on Social Networking Services

Voykinska, Violeta; Azenkot, Shiri; Wu, Shuo; Leshed, Gilly

doi:10.1145/2818048.2820013

Cited by 134 publications

(79 citation statements)

References 35 publications

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“…A number of previous user studies have investigated usability issues in accessibility in specific domains. Specifically, prior studies have identified usability and accessibility issues in JAWS SR [28], exercise tracking devices [26], and in particular applications, including social media, email clients, and course management systems [15, 24, 31, 32]. Ahmed et al study issues in privacy and security facing blind users [9].…”

Section: Related Workmentioning

confidence: 99%

Ubiquitous Accessibility for People with Visual Impairments

Billah

Ashok

Porter

et al. 2017

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

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Ubiquitous access is an increasingly common vision of computing, wherein users can interact with any computing device or service from anywhere, at any time. In the era of personal computing, users with visual impairments required special-purpose, assistive technologies, such as screen readers, to interact with computers. This paper investigates whether technologies like screen readers have kept pace with, or have created a barrier to, the trend toward ubiquitous access, with a specific focus on desktop computing as this is still the primary way computers are used in education and employment. Towards that, the paper presents a user study with 21 visually-impaired participants, specifically involving the switching of screen readers within and across different computing platforms, and the use of screen readers in remote access scenarios. Among the findings, the study shows that, even for remote desktop access—an early forerunner of true ubiquitous access—screen readers are too limited, if not unusable. The study also identifies several accessibility needs, such as uniformity of navigational experience across devices, and recommends potential solutions. In summary, assistive technologies have not made the jump into the era of ubiquitous access, and multiple, inconsistent screen readers create new practical problems for users with visual impairments.

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Section: Related Workmentioning

confidence: 99%

Ubiquitous Accessibility for People with Visual Impairments

Billah

Ashok

Porter

et al. 2017

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

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“…D ESCRIBING visual contents with natural language automatically has received increasing attention in both the computer vision and natural language processing communities. It can be applied in various practical applications, such as image and video retrieval [1], [2], [3], [4], [5], answering questions from images [6], and assisting people who suffer from vision disorders [7].…”

Section: Introductionmentioning

confidence: 99%

Reconstruct and Represent Video Contents for Captioning via Reinforcement Learning

Zhang

Wang

et al. 2020

IEEE Trans. Pattern Anal. Mach. Intell.

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In this paper, the problem of describing visual contents of a video sequence with natural language is addressed. Unlike previous video captioning work mainly exploiting the cues of video contents to make a language description, we propose a reconstruction network (RecNet) in a novel encoder-decoder-reconstructor architecture, which leverages both forward (video to sentence) and backward (sentence to video) flows for video captioning. Specifically, the encoder-decoder component makes use of the forward flow to produce a sentence description based on the encoded video semantic features. Two types of reconstructors are subsequently proposed to employ the backward flow and reproduce the video features from local and global perspectives, respectively, capitalizing on the hidden state sequence generated by the decoder. Moreover, in order to make a comprehensive reconstruction of the video features, we propose to fuse the two types of reconstructors together. The generation loss yielded by the encoder-decoder component and the reconstruction loss introduced by the reconstructor are jointly cast into training the proposed RecNet in an end-to-end fashion. Furthermore, the RecNet is fine-tuned by CIDEr optimization via reinforcement learning, which significantly boosts the captioning performance. Experimental results on benchmark datasets demonstrate that the proposed reconstructor can boost the performance of video captioning consistently.

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“…Sharing memories and experiences via photos is a common way to engage with others on social networking services (SNSs) [39,46,51]. For instance, Facebook users uploaded more than 350 million photos a day [24] and Twitter, which initially supported only text in tweets, now has more than 28.4% of tweets containing images [39].…”

Section: Introductionmentioning

confidence: 99%

“…The descriptions are normally invisible. We show it visually to demonstrate the design.While they want to share photos with others, visually impaired people find it difficult to understand the contents of photos and select good photos to post from their albums [30,47]. If a visually impaired person takes a photo and does not upload it immediately, it is hard for her to navigate through the album and find that photo independently, especially when many photos have accumulated in her album over time.Moreover, it is difficult to judge the quality of a photo, for example, to determine whether the photo is blurry, whether a person has her eyes closed in the photo, or whether the photo is aesthetically pleasing [30].Researchers and designers have tackled this problem, proposing techniques to help people with visual impairments access and understand the contents of a photo.…”

mentioning

confidence: 99%

The Effect of Computer-Generated Descriptions on Photo-Sharing Experiences of People with Visual Impairments

Zhao

Reynolds

et al. 2017

Proc. ACM Hum.-Comput. Interact.

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Like sighted people, visually impaired people want to share photographs on social networking services, but find it difficult to identify and select photos from their albums. We aimed to address this problem by incorporating state-of-the-art computer-generated descriptions into Facebook's photo-sharing feature. We interviewed 12 visually impaired participants to understand their photo-sharing experiences and designed a photo description feature for the Facebook mobile application. We evaluated this feature with six participants in a seven-day diary study. We found that participants used the descriptions to recall and organize their photos, but they hesitated to upload photos without a sighted person's input. In addition to basic information about photo content, participants wanted to know more details about salient objects and people, and whether the photos reflected their personal aesthetic. We discuss these findings from the lens of self-disclosure and self-presentation theories and propose new computer vision research directions that will better support visual content sharing by visually impaired people.CCS Concepts: • Information interfaces and presentations → Multimedia and information systems; • Social and professional topics → People with disabilities Fig. 1. Computer-generated descriptions in Facebook. The text in the white boxes is the descriptions that are read to a blind user by TalkBack. The descriptions are normally invisible. We show it visually to demonstrate the design.While they want to share photos with others, visually impaired people find it difficult to understand the contents of photos and select good photos to post from their albums [30,47]. If a visually impaired person takes a photo and does not upload it immediately, it is hard for her to navigate through the album and find that photo independently, especially when many photos have accumulated in her album over time.Moreover, it is difficult to judge the quality of a photo, for example, to determine whether the photo is blurry, whether a person has her eyes closed in the photo, or whether the photo is aesthetically pleasing [30].Researchers and designers have tackled this problem, proposing techniques to help people with visual impairments access and understand the contents of a photo. Most of these efforts used human-powered services (e.g., crowd workers, friends) to provide photo descriptions or answer a photo-based question [13,15,54,55]. However, such systems are hard to scale and sustain due to the limited number of volunteers, the monetary cost of crowd workers, and the possible social costs involved when asking friends [18,22]. Also, since there can be private information in local photos without the user knowing it, human-powered services also exposed visually impaired users to high privacy risks when sending personal photos to human assistants [16]. Therefore, other approaches are necessary for captioning a number of personal photos from a user's album in a photo-sharing use case.Recent research by Wu et al. presented automatic al...

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How Blind People Interact with Visual Content on Social Networking Services

Cited by 134 publications

References 35 publications

Ubiquitous Accessibility for People with Visual Impairments

Ubiquitous Accessibility for People with Visual Impairments

Reconstruct and Represent Video Contents for Captioning via Reinforcement Learning

The Effect of Computer-Generated Descriptions on Photo-Sharing Experiences of People with Visual Impairments

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