Image classification using super-vector coding of local image descriptors

Authors:
Xi Zhou;Kai Yu;Tong Zhang;Thomas S. Huang
Affiliations:
Dept. of ECE, University of Illnois at Urbana-Champaign;NEC Laboratories America, Cupertino, CA;Department of Statistics, Rutgers University;Dept. of ECE, University of Illnois at Urbana-Champaign
Venue:
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Year:
2010

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Abstract

This paper introduces a new framework for image classification using local visual descriptors. The pipeline first performs a non-linear feature transformation on descriptors, then aggregates the results together to form image-level representations, and finally applies a classification model. For all the three steps we suggest novel solutions which make our approach appealing in theory, more scalable in computation, and transparent in classification. Our experiments demonstrate that the proposed classification method achieves state-of-the-art accuracy on the well-known PASCAL benchmarks.