Pandora: Description of a Painting Database for Art Movement Recognition with Baselines and Perspectives

To facilitate computer analysis of visual art, in the form of paintings, we introduce Pandora (Paintings Dataset for Recognizing the Art movement) database, a collection of digitized paintings labelled with respect to the artistic movement. Noting that the set of databases available as benchmarks for evaluation is highly reduced and most existing ones are limited in variability and number of images, we propose a novel large scale dataset of digital paintings. The database consists of more than 7700 images from 12 art movements. Each genre is illustrated by a number of images varying from 250 to nearly 1000. We investigate how local and global features and classification systems are able to recognize the art movement. Our experimental results suggest that accurate recognition is achievable by a combination of various categories.To facilitate computer analysis of visual art, in the form of paintings, we introduce Pandora (Paintings Dataset for Recognizing the Art movement) database, a collection of digitized paintings labelled with respect to the artistic movement. Noting that the set of databases available as benchmarks for evaluation is highly reduced and most existing ones are limited in variability and number of images, we propose a novel large scale dataset of digital paintings. The database consists of more than 7700 images from 12 art movements. Each genre is illustrated by a number of images varying from 250 to nearly 1000. We investigate how local and global features and classification systems are able to recognize the art movement. Our experimental results suggest that accurate recognition is achievable by a combination of various categories.Comment: 11 pages, 1 figure, 6 table

Relate that image: A tool for finding related cultural heritage images

Museums,galleries, art centers, etc. are increasingly seeing the benefits of digitalizing their art work collections –and acting on it. The more visible benefits usually have to do with advertising, involving the citizens, or creating interactive tools that get people interested in coming to museums or buying art. With the availability of these increasingly large collections, analysis of art images has gained attention from researchers.This master thesis proposes a tool to recommend paintingsthat are similar to a given image of an artwork. We define different similarity measures that include criteria existent in the metadata associated with the digitized pictures (e.g. style, genre, artist, etc.), but also image content similarity. The work is more closely related to existing approaches on automatic classification of paintings, but also shares techniques with other areas such as image clustering. Our goal is to offer a tool that can enable creative uses, support the work of gallery / museum curators, help create interesting and interactive educational content, or create clusters of images as training sets for further learning and analysis algorithms

Painting-to-3D Model Alignment Via Discriminative Visual Elements

International audienceThis paper describes a technique that can reliably align arbitrary 2D depictions of an architectural site, including drawings, paintings and historical photographs, with a 3D model of the site. This is a tremendously difficult task as the appearance and scene structure in the 2D depictions can be very different from the appearance and geometry of the 3D model, e.g., due to the specific rendering style, drawing error, age, lighting or change of seasons. In addition, we face a hard search problem: the number of possible alignments of the painting to a large 3D model, such as a partial reconstruction of a city, is huge. To address these issues, we develop a new compact representation of complex 3D scenes. The 3D model of the scene is represented by a small set of discriminative visual elements that are automatically learnt from rendered views. Similar to object detection, the set of visual elements, as well as the weights of individual features for each element, are learnt in a discriminative fashion. We show that the learnt visual elements are reliably matched in 2D depictions of the scene despite large variations in rendering style (e.g. watercolor, sketch, historical photograph) and structural changes (e.g. missing scene parts, large occluders) of the scene. We demonstrate an application of the proposed approach to automatic re-photography to find an approximate viewpoint of historical paintings and photographs with respect to a 3D model of the site. The proposed alignment procedure is validated via a human user study on a new database of paintings and sketches spanning several sites. The results demonstrate that our algorithm produces significantly better alignments than several baseline methods

Perceptual, semantic and affective dimensions of experience of abstract and representational paintings

In this study the difference between representational and abstract paintings in judgments on perceptual, semantic and affective dimensions was investigated. Two groups of participants judged the sets of representational and abstract paintings on three groups of dimensions: perceptual (Form, Color, Space and Complexity), semantic (Illusion-Construction of Reality, Expression, Ideology and Decoration), and affective (Hedonic Tone, Arousal, Relaxation and Regularity). The results have shown that representational paintings have higher judgments on the perceptual dimensions of Form and Complexity, the semantic dimension of the Illusion of Reality (the opposite pole of the Construction of Reality), and the affective dimension of Regularity. On the other hand, abstract paintings have higher judgments on the perceptual dimension of Color, the semantic dimensions of Construction of Reality (the opposite pole of the Illusion of Reality) and Expression, and the affective dimension Arousal. A discriminant analysis indicated that all three sets of dimensions are relatively good predictors of the classification of representational and abstract paintings (61-100%). The results suggest that the subjective categorization of paintings is generally based on the recognizability of pictorial content (representational vs. abstract), but some formal or stylistic properties play a role in the categorization, as well: some expressionistic representational paintings were classified in an abstract category, and some geometrically abstract paintings were classified as representational

Spartan Daily, September 8, 1978

Volume 71, Issue 4https://scholarworks.sjsu.edu/spartandaily/6363/thumbnail.jp

Power, identity and antiquarian approaches in modern Chinese art

The pursuit of antiquity was important for scholarly artists in constructing their knowledge of history and cultural identity in late Imperial China. Following various publications by Bi Yuan 畢沅 (1730-1797), Wu Yi 武億 (1745-1799) and Qian Daxin 錢大昕 (1728-1804) in the 18th century, the study and collecting of rubbings of Northern Wei stone inscriptions and steles was popular. Such spread of interest in jinshi, inscriptions on metal and stone, also formed a base for studying seal carving, epigraphy and archaic painting. While traditional antiquarians would cherish inscriptions which enabled them to correct mistakes in the transmitted historical texts and the Classics, however, much of the antiquarian activity was adapted to mere literary exercise or connoisseurship, for instance, to supplying materials which could provide models for seal-carving and calligraphy. Examples could be seen in the calligraphy works and seal carvings of the Xiling bajia 西泠八家 (Eight Masters of Xiling, i.e. Hangzhou), also known as Zhe School of Calligraphy and Carving. Their keen interest in seeking inspiration from steles for their artistic presentations has been recorded in their writing and painting. In addition, the way the scholar-collector of the 19th and early 20th centuries mounted the rubbings, seals, inscriptions, paintings, letters and textual evidence studies into one album shows a changing ideology: rubbings were not only for scholarly study in classical learning, but were regarded as part of the art form and were appreciated on various social occasions. The antiquarian movement ultimately served as a tool for re-writing art historiography in modern China. This paper aims to address the phenomenon and formation of the jinshi painting that dominated in late Imperial and early modern China. Through case studies of three important jinshi societies in Shanghai, I will investigate in what way literary taste from the southern region gradually replaced imperial patronage which was in decline after the Qianlong emperor’s reign, and how the shift of the cultural centre from Beijing to the southern regions from the mid-19th century onwards became a reflection of changing power and identity for cultural leaders and their perspectives in history and the history of objects

Printed texture guided color feature fusion for impressionism style rendering of oil paintings.

As a major branch of Non-Photorealistic Rendering (NPR), image stylization mainly uses computer algorithms to render a photo into an artistic painting. Recent work has shown that the ex-traction of style information such as stroke texture and color of the target style image is the key to image stylization. Given its stroke texture and color characteristics, a new stroke rendering method is proposed. By fully considering the tonal characteristics and the representative color of the original oil painting, it can fit the tone of the original oil painting image into a stylized image whilst keeping the artist's creative effect. The experiments have validated the efficacy of the proposed model in comparison to three state-of-the-arts. This method would be more suitable for the works of pointillism painters with a relatively uniform style, especially for natural scenes, otherwise, the results can be less satisfactory