Color multi-fusion fisher vector feature for fine art painting categorization and influence analysis

Ajit Puthenputhussery, Qingfeng Liu, Chengjun Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

Abstract

This paper presents a novel set of image features that encode the local, color, spatial, relative intensity information and gradient orientation of the painting image for painting artist classification, style classification as well as artist and style influence analysis. In particular, a new color DAISY Fisher vector (CD-FV) feature is first created by computing Fisher vectors on densely sampled DAISY features. Second, a color WLD-SIFT Fisher vector (CWS-FV) feature is developed by fusing Weber local descriptors (WLD) with Scale Invariant Feature Transform (SIFT) descriptors and Fisher vectors are computed on the fused WLD-SIFT features. Finally, an innovative color multi-fusion Fisher vector (CMFFV) feature is developed by integrating the Principal Component Analysis (PCA) features of CD-FV, CWS-FV and color SIFT-FV features. The effectiveness of the proposed CMFFV feature is assessed on the challenging Painting-91 dataset. Experimental results show that the proposed CMFFV feature is able to (i) achieve the state-of-the-art performance for painting artist classification, (ii) outperform other popular image descriptors, as well as (iii) discover the artist and style influence to understand their connections and evolution in different art movement periods.

Original languageEnglish (US)
Title of host publication2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509006410
DOIs
StatePublished - May 23 2016
EventIEEE Winter Conference on Applications of Computer Vision, WACV 2016 - Lake Placid, United States
Duration: Mar 7 2016Mar 10 2016

Publication series

Name2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016

Other

OtherIEEE Winter Conference on Applications of Computer Vision, WACV 2016
Country/TerritoryUnited States
CityLake Placid
Period3/7/163/10/16

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

Fingerprint

Dive into the research topics of 'Color multi-fusion fisher vector feature for fine art painting categorization and influence analysis'. Together they form a unique fingerprint.

Cite this