Towards optimal bag-of-features for object categorization and semantic video retrieval

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)

415 Scopus Citations
View graph of relations

Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings of the 6th ACM International Conference on Image and Video Retrieval, CIVR 2007
Pages494-501
StatePublished - 2007

Conference

Title6th ACM International Conference on Image and Video Retrieval, CIVR 2007
PlaceNetherlands
CityAmsterdam
Period9-11 July 2007

Abstract

Bag-of-features (BoF) deriving from local keypoints has recently appeared promising for object and scene classification. Whether BoF can naturally survive the challenges such as reliability and scalability of visual classification, nevertheless, remains uncertain due to various implementation choices. In this paper, we evaluate various factors which govern the performance of BoF. The factors include the choices of detector, kernel, vocabulary size and weighting scheme. We offer some practical insights in how to optimize the performance by choosing good keypoint detector and kernel. For the weighting scheme, we propose a novel soft-weighting method to assess the significance of a visual word to an image. We experimentally show that the proposed soft-weighting scheme can consistently offer better performance than other popular weighting methods. On both PASCAL-2005 and TRECVID-2006 datasets, our BoF setting generates competitive performance compared to the state-of-the-art techniques. We also show that the BoF is highly complementary to global features. By incorporating the BoF with color and texture features, an improvement of 50% is reported on TRECVID-2006 dataset. Copyright 2007 ACM.

Research Area(s)

  • Bag-of-features, Kernel, Keypoint detector, Object categorization, Semantic video retrieval, Soft-weighting

Citation Format(s)

Towards optimal bag-of-features for object categorization and semantic video retrieval. / Jiang, Yu-Gang; Ngo, Chong-Wah; Yang, Jun.

Proceedings of the 6th ACM International Conference on Image and Video Retrieval, CIVR 2007. 2007. p. 494-501.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)