Feedback is Needed for Retakes: An Explainable Poor Image Notification Framework for the Visually Impaired

Autor:	Ohata, Kazuya, Kitada, Shunsuke, Iyatomi, Hitoshi
Rok vydání:	2022
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Artificial Intelligence Computer Science - Computation and Language Computer Science - Human-Computer Interaction Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	We propose a simple yet effective image captioning framework that can determine the quality of an image and notify the user of the reasons for any flaws in the image. Our framework first determines the quality of images and then generates captions using only those images that are determined to be of high quality. The user is notified by the flaws feature to retake if image quality is low, and this cycle is repeated until the input image is deemed to be of high quality. As a component of the framework, we trained and evaluated a low-quality image detection model that simultaneously learns difficulty in recognizing images and individual flaws, and we demonstrated that our proposal can explain the reasons for flaws with a sufficient score. We also evaluated a dataset with low-quality images removed by our framework and found improved values for all four common metrics (e.g., BLEU-4, METEOR, ROUGE-L, CIDEr), confirming an improvement in general-purpose image captioning capability. Our framework would assist the visually impaired, who have difficulty judging image quality. Comment: 6 pages, 4 figures. Accepted at 2022 IEEE 19th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) as a full paper
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2211.09427 Zobrazit plný text záznamu View this record from Arxiv