Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICME.2010.5583896
Title: Evaluation of histogram based interest point detector in web image classification and search
Authors: Cai, J.
Zha, Z.-J. 
Zhao, Y.
Wang, Z.
Keywords: Bag of visual word
Histogram based
Interest point detector
Local feature
Issue Date: 2010
Source: Cai, J., Zha, Z.-J., Zhao, Y., Wang, Z. (2010). Evaluation of histogram based interest point detector in web image classification and search. 2010 IEEE International Conference on Multimedia and Expo, ICME 2010 : 613-618. ScholarBank@NUS Repository. https://doi.org/10.1109/ICME.2010.5583896
Abstract: Local image feature has received increasing attention in various applications, such as web image classification and search. The process of local feature extraction consists of two main steps: interest point detection and local feature description. A wealth of interest point detectors have been proposed in last decades. Most of them measure pixel-wise differences in image intensity or color. Recently, a new type of interest point detector has been developed, which incorporates histogram-based representation into the process of interest point detection. In this paper, we evaluate this histogram-based interest point detector in the context of web image classification and search, as well as compare it against typical pixel-based detectors and heuristic grid-based detector. The evaluation is performed on two web image datasets: NUS-WIDE-OBJECT and MIRFLICKR-25000 datasets. The experimental results demonstrate that the histogram-based interest point detector outperforms the pixelbased and grid-based detectors in both web image classification and search tasks. © 2010 IEEE.
Source Title: 2010 IEEE International Conference on Multimedia and Expo, ICME 2010
URI: http://scholarbank.nus.edu.sg/handle/10635/40453
ISBN: 9781424474912
DOI: 10.1109/ICME.2010.5583896
Appears in Collections:Staff Publications

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