Image collector III: a web image-gathering system with bag-of-keypoints

ABSTRACT

We propose a new system to mine visual knowledge on the Web.There are huge image data as well as text data on the Web. However, mining image data from the Web is paid less attention than mining text data, since treating semantics of images are much more difficult. In this paper, we propose introducing a latest image recognition technique, which is the bag-of-keypoints representation,into Web image-gathering task. By the experiments we show theproposed system outperforms our previous systems and Google Imagesearch greatly.

REFERENCES

• 1: G. Csurka, C. Bray, C. Dance, and L. Fan. Visual categorization with bags of keypoints. In Proc. of ECCV Workshop on Statistical Learning in Computer Vision, pages 1--22, 2004.
• 2: David G. Lowe, Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, v.60 n.2, p.91-110, November 2004 [doi>10.1023/B:VISI.0000029664.99615.94]
• 3: Keiji Yanai, Generic image classification using visual knowledge on the web, Proceedings of the eleventh ACM international conference on Multimedia, November 02-08, 2003, Berkeley, CA, USA [doi>10.1145/957013.957047]
• 4: K. Yanai. Image collector II : An over-one-thousand-image-gathering system. In Proc. of the Twelfth International World Wide Web Conference, 2003.
• 5: Keiji Yanai , Kobus Barnard, Probabilistic web image gathering, Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval, November 10-11, 2005, Hilton, Singapore [doi>10.1145/1101826.1101838]

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.m Miscellaneous

General Terms:
Algorithms, Experimentation, Measurement

Keywords:
bag-of-keypoints, image recognition, web image mining