Karido: A GWAP for telling artworks apart

International Journal of Engineering Sciences & Research Technology, 2014

The vast resource of pictures available on the web and the fact that many of them naturally co-occur with topically related documents and are captioned we focus on the task of automatically generating captions for images, here the model learns to create captions from a database of news articles, and the pictures embedded in them, and their captions, and consists of two stages. Content selection identifies what the image and accompanying article are about, whereas surface realization determines how to verbalize the chosen content. We approximate content selection with a probabilistic image annotation model that suggests keywords for an image. In the Proposed system extensive features are extracted from the database images and stored in the feature library. The extensive features set is comprised of shape features along with the color, texture and the contour let features, which are utilized in this work. When a query image is given, the features are extracted in the similar fashion. Subsequently, GA-based similarity measure is performed between the query image features and the database image features.

Multimedia Systems, 2010

In this paper we present the Name-It-Game, an interactive multimedia game fostering the swift creation of a large data set of region-based image annotations. Compared to existing annotation games, we consider an added semantic structure, by means of the WordNet ontology, the main innovation of the Name-It-Game. Using an ontologypowered game, instead of the more traditional annotation tools, potentially makes region-based image labeling more fun and accessible for every type of user. However, the current games often present the players with hard-to-guess objects. To prevent this from happening in the Name-It-Game, we successfully identify WordNet categories which filter out hard-to-guess objects. To verify the speed of the annotation process, we compare the online Name-It-Game with a desktop tool with similar features. Results show that the Name-It-Game outperforms this tool for semantic region-based image labeling. Lastly, we measure the accuracy of the produced segmentations and compare them with carefully created LabelMe segmentations. Judging from the quantitative and qualitative results, we believe the segmentations are competitive to those of LabelMe, especially when averaged over multiple games. By adding semantics to region-based image annotations, using the Name-It-Game, we have opened up an efficient means to provide precious labels in a playful manner.

2020 International Joint Conference on Neural Networks (IJCNN), 2020

In this paper, we deal with the problem of automatic tag recommendation for painting artworks. Diachronic descriptions containing deviations on the vocabulary used to describe each painting usually occur when the work is done by many experts over time. The objective of this work is to provide a framework that produces a more accurate and homogeneous set of tags for each painting in a large collection. To validate our method we build a model based on a weakly-supervised neural network for over 5,300 paintings with hand-labeled descriptions made by experts for the paintings of the Brazilian painter Candido Portinari. This work takes place with the Portinari Project which started in 1979 intending to recover and catalog the paintings of the Brazilian painter. The Portinari paintings at that time were in private collections and museums spread around the world and thus inaccessible to the public. The descriptions of each painting were made by a large number of collaborators over 40 years...

ACM Transactions on Multimedia Computing, Communications, and Applications, 2013

Interactive tagging is an approach that combines human and computer to assign descriptive keywords to image contents in a semi-automatic way. It can avoid the problems in automatic tagging and pure manual tagging by achieving a compromise between tagging performance and manual cost. However, conventional research efforts on interactive tagging mainly focus on sample selection and models for tag prediction. In this work, we investigate interactive tagging from a different aspect. We introduce an interactive image tagging framework that can more fully make use of human's labeling efforts. That means, it can achieve a specified tagging performance by taking less manual labeling effort or achieve better tagging performance with a specified labeling cost. In the framework, hashing is used to enable a quick clustering of image regions and a dynamic multiscale clustering labeling strategy is proposed such that users can label a large group of similar regions each time. We also employ a...

2010

– In this paper we present a classification of color harmonies and contrasts, which is consistent with human perceiving of visual expression. It is conformed to the possibilities of automatic extraction of visual information from digitalized copies of art images. The classification is done on the base of the three main characteristics of the color most closed to the human perception – hue, saturation and lightness. Functions for automatic features extraction from digital images are defined. These functions are realized as part of a virtual laboratory "Art Painting Image Color Aesthetic and Semantic " (APICAS). The system can be used by designers and art students for searching images, having certain harmonies or contrasts in image collections as well as a for examining specifics of artists or movements. In future we will use the system as a Web 2.0 service, which could be included in a virtual learning environment.

2020

It would be hard to overstate the importance of Computer Vision (CV), applications of which can be found from self-driving cars, through facial recognition to augmented reality and the healthcare industry. Recent years have witnessed dramatic progress in visual-object recognition, partially ascribable to the availability of labeled data. Unfortunately, recognition of obscure, unclear and ambiguous photos that are taken from unusual angles or distances remains a major challenge, as recently shown by the creation of the ObjectNet [1]. This paper complements that work via a game in which obscure, unclear and ambiguous photos are collaboratively created and labeled by the players, who adopt the role of detectives collecting evidence against in-game criminals. The game rules enforce the creation of images that are challenging to identify for CV and people alike, as a means of ensuring the high quality of players' input.

2009

In this paper we present a classification of color harmonies and contrasts, which is consistent with human perceiving of visual expression. It is conformed to the possibilities of automatic extraction of visual information from digitalized copies of art images. The classification is done on the base of the three main characteristics of the color most closed to the human perception -hue, saturation and lightness. Functions for automatic features extraction from digital images are defined. These functions are realized as part of a virtual laboratory "Art Painting Image Color Aesthetic and Semantic" (APICAS). The system can be used by designers and art students for searching images, having certain harmonies or contrasts in image collections as well as a for examining specifics of artists or movements. In future we will use the system as a Web 2.0 service, which could be included in a virtual learning environment.

2011

In this paper we present a classification of color harmonies and contrasts, which is consistent with human perceiving of visual expression. It is conformed to the possibilities of automatic extraction of visual information from digitalized copies of art images. The classification is done on the base of the three main characteristics of the color most closed to the human perception -hue, saturation and lightness. Functions for automatic features extraction from digital images are defined. These functions are realized as part of a virtual laboratory "Art Painting Image Color Aesthetic and Semantic" (APICAS). The system can be used by designers and art students for searching images, having certain harmonies or contrasts in image collections as well as a for examining specifics of artists or movements. In future we will use the system as a Web 2.0 service, which could be included in a virtual learning environment.

Journal of the American Society for Information Science and Technology, 2011

Applications that use games to harness human intelligence to perform various computational tasks are increasing in popularity and may be termed as human computation games (HCGs).

2009

Page 1. Style Modeling for Tagging Personal Photo Collections Manni Duan Dept. of EEIS, USTC Hefei, China mnduan@mail.ustc.edu.cn Adrian Ulges German Research Center for Artificial Intelligence (DFKI) Kaiserslautern, Germany ulges@iupr.dfki.de Thomas M. Breuel DFKI and TU Kaiserslautern Kaiserslautern, Germany tmb@iupr.dfki.de Xiu-qing Wu Dept.