Videoader: a video advertising system based on intelligent analysis of visual content
Proceedings of the Third International Conference on Internet Multimedia Computing and Service
Proceedings of the 20th ACM international conference on Multimedia
Personalized image recommendation and retrieval via latent SVM based model
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
Advertising object in web videos
Neurocomputing
A novel framework for concept detection on large scale video database and feature pool
Artificial Intelligence Review
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There are about 8% of men and 0.8% of women suffering from colorblindness. Due to the loss of certain color information, regions or objects in several images cannot be recognized by these viewers and this may degrade their perception and understanding of the images. This paper introduces an in-image accessibility indication scheme, which aims to automatically point out regions in which the content can hardly be recognized by colorblind viewers in a manually designed image. The proposed method first establishes a set of points around which the patches are not prominent enough for colorblind viewers due to the loss of color information. The inaccessible regions are then detected based on these points via a regularization framework. This scheme can be applied to check the accessibility of designed images, and consequently it can be used to help designers improve the images, such as modifying the colors of several objects or components. To our best knowledge, this is the first work that attempts to detect regions with accessibility problems in images for colorblindness. Experiments are conducted on 1994 poster images and empirical results have demonstrated the effectiveness of our approach.