Ask the dictionary: Soft-assignment location-orientation pooling for image classification

Qilong Wang, Xiaona Deng, Peihua Li, Lei Zhang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

The pooling step is one of the key components of the well-known Bag-of-visual words (BoW) model widely used in image classification. In this paper, we propose a novel pooling method, which is called Soft-Assignment Location-Orientation Pooling (SALOP). Inspired by the bag of statistical sampling analysis (Bossa), SALOP also explores the effect of dictionary for pooling method, but leverages both location and orientation information between the local descriptors and the atoms of dictionary to aggregate feature codes. Moreover, different from existing pooling methods, SALOP employs a soft-assignment pooling scheme to handle ambiguity and uncertainty existing in the pooling process. The evaluation is conducted on two image benchmarks: Scene15 and PASCAL VOC 2007. The experimental results show our SALOP can achieve promising performances.
Original languageEnglish
Title of host publication2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
PublisherIEEE Computer Society
Pages4570-4574
Number of pages5
Volume2015-December
ISBN (Electronic)9781479983391
DOIs
Publication statusPublished - 9 Dec 2015
EventIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
Duration: 27 Sep 201530 Sep 2015

Conference

ConferenceIEEE International Conference on Image Processing, ICIP 2015
CountryCanada
CityQuebec City
Period27/09/1530/09/15

Keywords

  • Bag-of-visual words
  • dictionary
  • Image classification
  • location-orientation pooling
  • soft-assignment

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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