Imperial College London

DrKrystianMikolajczyk

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Reader in Computer Vision
 
 
 
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Contact

 

+44 (0)20 7594 6220k.mikolajczyk

 
 
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Location

 

Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Gaur:2014:10.1109/ICPR.2014.587,
author = {Gaur, A and Mikolajczyk, K},
doi = {10.1109/ICPR.2014.587},
pages = {3410--3415},
title = {Ranking images based on aesthetic qualities},
url = {http://dx.doi.org/10.1109/ICPR.2014.587},
year = {2014}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - © 2014 IEEE. We propose a novel approach for learning image representation based on qualitative assessments of visual aesthetics. It relies on a multi-node multi-state model that represents image attributes and their relations. The model is learnt from pair wise image preferences provided by annotators. To demonstrate the effectiveness we apply our approach to fashion image rating, i.e., comparative assessment of aesthetic qualities. Bag-of-features object recognition is used for the classification of visual attributes such as clothing and body shape in an image. The attributes and their relations are then assigned learnt potentials which are used to rate the images. Evaluation of the representation model has demonstrated a high performance rate in ranking fashion images.
AU - Gaur,A
AU - Mikolajczyk,K
DO - 10.1109/ICPR.2014.587
EP - 3415
PY - 2014///
SN - 1051-4651
SP - 3410
TI - Ranking images based on aesthetic qualities
UR - http://dx.doi.org/10.1109/ICPR.2014.587
ER -