Video Question Answering for People with Visual Impairments Using an Egocentric 360-Degree Camera
<|reference_start|>Video Question Answering for People with Visual Impairments Using an Egocentric 360-Degree Camera: This paper addresses the daily challenges encountered by visually impaired individuals, such as limited access to information, navigation difficulties, and barriers to social interaction. To alleviate these challenges, we introduce a novel visual question answering dataset. Our dataset offers two significant advancements over previous datasets: Firstly, it features videos captured using a 360-degree egocentric wearable camera, enabling observation of the entire surroundings, departing from the static image-centric nature of prior datasets. Secondly, unlike datasets centered on singular challenges, ours addresses multiple real-life obstacles simultaneously through an innovative visual-question answering framework. We validate our dataset using various state-of-the-art VideoQA methods and diverse metrics. Results indicate that while progress has been made, satisfactory performance levels for AI-powered assistive services remain elusive for visually impaired individuals. Additionally, our evaluation highlights the distinctive features of the proposed dataset, featuring ego-motion in videos captured via 360-degree cameras across varied scenarios.<|reference_end|>
@article{song2024video,
    title={Video Question Answering for People with Visual Impairments Using an
  Egocentric 360-Degree Camera},
    author={Inpyo Song, Minjun Joo, Joonhyung Kwon and Jangwon Lee},
    journal={arXiv preprint arXiv:2405.19794},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.19794},
    primaryClass={cs.CV}
}