TY - GEN
T1 - Understanding and predicting importance in images
AU - Berg, Alexander C.
AU - Berg, Tamara L.
AU - Daume, Hal
AU - Dodge, Jesse
AU - Goyal, Amit
AU - Han, Xufeng
AU - Mensch, Alyssa
AU - Mitchell, Margaret
AU - Sood, Aneesh
AU - Stratos, Karl
AU - Yamaguchi, Kota
PY - 2012
Y1 - 2012
N2 - What do people care about in an image? To drive computational visual recognition toward more human-centric outputs, we need a better understanding of how people perceive and judge the importance of content in images. In this paper, we explore how a number of factors relate to human perception of importance. Proposed factors fall into 3 broad types: 1) factors related to composition, e.g. size, location, 2) factors related to semantics, e.g. category of object or scene, and 3) contextual factors related to the likelihood of attribute-object, or object-scene pairs. We explore these factors using what people describe as a proxy for importance. Finally, we build models to predict what will be described about an image given either known image content, or image content estimated automatically by recognition systems.
AB - What do people care about in an image? To drive computational visual recognition toward more human-centric outputs, we need a better understanding of how people perceive and judge the importance of content in images. In this paper, we explore how a number of factors relate to human perception of importance. Proposed factors fall into 3 broad types: 1) factors related to composition, e.g. size, location, 2) factors related to semantics, e.g. category of object or scene, and 3) contextual factors related to the likelihood of attribute-object, or object-scene pairs. We explore these factors using what people describe as a proxy for importance. Finally, we build models to predict what will be described about an image given either known image content, or image content estimated automatically by recognition systems.
UR - http://www.scopus.com/inward/record.url?scp=84866726859&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84866726859&partnerID=8YFLogxK
U2 - 10.1109/CVPR.2012.6248100
DO - 10.1109/CVPR.2012.6248100
M3 - Conference contribution
AN - SCOPUS:84866726859
SN - 9781467312264
T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
SP - 3562
EP - 3569
BT - 2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012
T2 - 2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012
Y2 - 16 June 2012 through 21 June 2012
ER -