Matches in SemOpenAlex for { <https://semopenalex.org/work/W2149203771> ?p ?o ?g. }
- W2149203771 endingPage "27" @default.
- W2149203771 startingPage "1" @default.
- W2149203771 abstract "When artists express their feelings through the artworks they create, it is believed that the resulting works transform into objects with “emotions” capable of conveying the artists' mood to the audience. There is little to no dispute about this belief: Regardless of the artwork, genre, time, and origin of creation, people from different backgrounds are able to read the emotional messages. This holds true even for the most abstract paintings. Could this idea be applied to machines as well? Can machines learn what makes a work of art “emotional”? In this work, we employ a state-of-the-art recognition system to learn which statistical patterns are associated with positive and negative emotions on two different datasets that comprise professional and amateur abstract artworks. Moreover, we analyze and compare two different annotation methods in order to establish the ground truth of positive and negative emotions in abstract art. Additionally, we use computer vision techniques to quantify which parts of a painting evoke positive and negative emotions. We also demonstrate how the quantification of evidence for positive and negative emotions can be used to predict which parts of a painting people prefer to focus on. This method opens new opportunities of research on why a specific painting is perceived as emotional at global and local scales." @default.
- W2149203771 created "2016-06-24" @default.
- W2149203771 creator A5007465102 @default.
- W2149203771 creator A5020938231 @default.
- W2149203771 creator A5027028450 @default.
- W2149203771 creator A5027171279 @default.
- W2149203771 creator A5048393526 @default.
- W2149203771 creator A5062918523 @default.
- W2149203771 date "2015-06-30" @default.
- W2149203771 modified "2023-10-17" @default.
- W2149203771 title "Affective Analysis of Professional and Amateur Abstract Paintings Using Statistical Analysis and Art Theory" @default.
- W2149203771 cites W1552007786 @default.
- W2149203771 cites W1680439812 @default.
- W2149203771 cites W1835180891 @default.
- W2149203771 cites W188144184 @default.
- W2149203771 cites W1966560275 @default.
- W2149203771 cites W1985473256 @default.
- W2149203771 cites W1987252487 @default.
- W2149203771 cites W2000220044 @default.
- W2149203771 cites W2000813396 @default.
- W2149203771 cites W2003856922 @default.
- W2149203771 cites W2009627211 @default.
- W2149203771 cites W2034258736 @default.
- W2149203771 cites W2048835603 @default.
- W2149203771 cites W2052596350 @default.
- W2149203771 cites W2063948594 @default.
- W2149203771 cites W2064378963 @default.
- W2149203771 cites W2066941820 @default.
- W2149203771 cites W2072238630 @default.
- W2149203771 cites W2074356411 @default.
- W2149203771 cites W2075970457 @default.
- W2149203771 cites W2085940040 @default.
- W2149203771 cites W2090405960 @default.
- W2149203771 cites W2103666701 @default.
- W2149203771 cites W2109034349 @default.
- W2149203771 cites W2118087936 @default.
- W2149203771 cites W2119228922 @default.
- W2149203771 cites W2144548005 @default.
- W2149203771 cites W2149628368 @default.
- W2149203771 cites W2151103935 @default.
- W2149203771 cites W2151900481 @default.
- W2149203771 cites W2152532634 @default.
- W2149203771 cites W2153975459 @default.
- W2149203771 cites W2158030467 @default.
- W2149203771 cites W2162762921 @default.
- W2149203771 cites W2468518470 @default.
- W2149203771 cites W2795515831 @default.
- W2149203771 cites W3125067981 @default.
- W2149203771 doi "https://doi.org/10.1145/2768209" @default.
- W2149203771 hasPublicationYear "2015" @default.
- W2149203771 type Work @default.
- W2149203771 sameAs 2149203771 @default.
- W2149203771 citedByCount "34" @default.
- W2149203771 countsByYear W21492037712015 @default.
- W2149203771 countsByYear W21492037712016 @default.
- W2149203771 countsByYear W21492037712017 @default.
- W2149203771 countsByYear W21492037712018 @default.
- W2149203771 countsByYear W21492037712019 @default.
- W2149203771 countsByYear W21492037712020 @default.
- W2149203771 countsByYear W21492037712021 @default.
- W2149203771 countsByYear W21492037712022 @default.
- W2149203771 countsByYear W21492037712023 @default.
- W2149203771 crossrefType "journal-article" @default.
- W2149203771 hasAuthorship W2149203771A5007465102 @default.
- W2149203771 hasAuthorship W2149203771A5020938231 @default.
- W2149203771 hasAuthorship W2149203771A5027028450 @default.
- W2149203771 hasAuthorship W2149203771A5027171279 @default.
- W2149203771 hasAuthorship W2149203771A5048393526 @default.
- W2149203771 hasAuthorship W2149203771A5062918523 @default.
- W2149203771 hasBestOaLocation W21492037712 @default.
- W2149203771 hasConcept C107038049 @default.
- W2149203771 hasConcept C122980154 @default.
- W2149203771 hasConcept C142362112 @default.
- W2149203771 hasConcept C153349607 @default.
- W2149203771 hasConcept C15744967 @default.
- W2149203771 hasConcept C166957645 @default.
- W2149203771 hasConcept C180747234 @default.
- W2149203771 hasConcept C205783811 @default.
- W2149203771 hasConcept C2778044066 @default.
- W2149203771 hasConcept C2780733359 @default.
- W2149203771 hasConcept C41008148 @default.
- W2149203771 hasConcept C4320435 @default.
- W2149203771 hasConcept C77805123 @default.
- W2149203771 hasConcept C95457728 @default.
- W2149203771 hasConceptScore W2149203771C107038049 @default.
- W2149203771 hasConceptScore W2149203771C122980154 @default.
- W2149203771 hasConceptScore W2149203771C142362112 @default.
- W2149203771 hasConceptScore W2149203771C153349607 @default.
- W2149203771 hasConceptScore W2149203771C15744967 @default.
- W2149203771 hasConceptScore W2149203771C166957645 @default.
- W2149203771 hasConceptScore W2149203771C180747234 @default.
- W2149203771 hasConceptScore W2149203771C205783811 @default.
- W2149203771 hasConceptScore W2149203771C2778044066 @default.
- W2149203771 hasConceptScore W2149203771C2780733359 @default.
- W2149203771 hasConceptScore W2149203771C41008148 @default.
- W2149203771 hasConceptScore W2149203771C4320435 @default.
- W2149203771 hasConceptScore W2149203771C77805123 @default.
- W2149203771 hasConceptScore W2149203771C95457728 @default.