TY - GEN
T1 - Seeing people in social context
T2 - 11th European Conference on Computer Vision, ECCV 2010
AU - Wang, Gang
AU - Gallagher, Andrew
AU - Luo, Jiebo
AU - Forsyth, David
PY - 2010
Y1 - 2010
N2 - The people in an image are generally not strangers, but instead often share social relationships such as husband-wife, siblings, grandparent-child, father-child, or mother-child. Further, the social relationship between a pair of people influences the relative position and appearance of the people in the image. This paper explores using familial social relationships as context for recognizing people and for recognizing the social relationships between pairs of people. We introduce a model for representing the interaction between social relationship, facial appearance, and identity. We show that the family relationship a pair of people share influences the relative pairwise features between them. The experiments on a set of personal collections show significant improvement in people recognition is achieved by modeling social relationships, even in a weak label setting that is attractive in practical applications. Furthermore, we show the social relationships are effectively recognized in images from a separate test image collection.
AB - The people in an image are generally not strangers, but instead often share social relationships such as husband-wife, siblings, grandparent-child, father-child, or mother-child. Further, the social relationship between a pair of people influences the relative position and appearance of the people in the image. This paper explores using familial social relationships as context for recognizing people and for recognizing the social relationships between pairs of people. We introduce a model for representing the interaction between social relationship, facial appearance, and identity. We show that the family relationship a pair of people share influences the relative pairwise features between them. The experiments on a set of personal collections show significant improvement in people recognition is achieved by modeling social relationships, even in a weak label setting that is attractive in practical applications. Furthermore, we show the social relationships are effectively recognized in images from a separate test image collection.
UR - http://www.scopus.com/inward/record.url?scp=78149289570&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78149289570&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-15555-0_13
DO - 10.1007/978-3-642-15555-0_13
M3 - Conference contribution
AN - SCOPUS:78149289570
SN - 3642155545
SN - 9783642155543
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 169
EP - 182
BT - Computer Vision, ECCV 2010 - 11th European Conference on Computer Vision, Proceedings
PB - Springer
Y2 - 10 September 2010 through 11 September 2010
ER -