TY - GEN
T1 - Learning the consensus on visual quality for next-generation image management
AU - Datta, Ritendra
AU - Li, Jia
AU - Wang, James Z.
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - While personal and community-based image collections grow by the day, the demand for novel photo management capabilities grows with it. Recent research has shown that it is possible to learn the consensus on visual quality measures such as aesthetics with a moderate degree of success. Here, we seek to push this performance to more realistic levels and use it to (a) help select high-quality pictures from collections, and (b) eliminate low-quality ones, introducing appropriate performance metrics in each case. To achieve this, we propose a sequential arrangement of a weighted linear least squares regressor and a naive Bayes' classifier, applied to a set of visual features previously found useful for quality prediction. Experiments on real-world data for these tasks show promising performance, with significant improvements over a previously proposed SVM-based method.
AB - While personal and community-based image collections grow by the day, the demand for novel photo management capabilities grows with it. Recent research has shown that it is possible to learn the consensus on visual quality measures such as aesthetics with a moderate degree of success. Here, we seek to push this performance to more realistic levels and use it to (a) help select high-quality pictures from collections, and (b) eliminate low-quality ones, introducing appropriate performance metrics in each case. To achieve this, we propose a sequential arrangement of a weighted linear least squares regressor and a naive Bayes' classifier, applied to a set of visual features previously found useful for quality prediction. Experiments on real-world data for these tasks show promising performance, with significant improvements over a previously proposed SVM-based method.
UR - http://www.scopus.com/inward/record.url?scp=37849034092&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=37849034092&partnerID=8YFLogxK
U2 - 10.1145/1291233.1291364
DO - 10.1145/1291233.1291364
M3 - Conference contribution
AN - SCOPUS:37849034092
SN - 9781595937025
T3 - Proceedings of the ACM International Multimedia Conference and Exhibition
SP - 533
EP - 536
BT - Proceedings of the Fifteenth ACM International Conference on Multimedia, MM'07
T2 - 15th ACM International Conference on Multimedia, MM'07
Y2 - 24 September 2007 through 29 September 2007
ER -