Recent Progress in Image and Video Segmentation for CBVIR

Author:

Zhang Yu-Jin1

Affiliation:

1. Tsinghua University, Beijing, China

Abstract

A simple search from EI Compendex by using the term “image segmentation” only in title field could produce around 5000 records (Zhang, 2006). However, as no general theory for image segmentation for different application domains, particular algorithms have been developed. The domain of Content-Based Image Retrieval (CBIR) is such a typical example, where many specific techniques have been proposed. An introduction focused on research works before 2004 can be found in Zhang (2005). This paper is an up-to-date and extended version from CBIR to CBVIR (Content-Based Visual Information Retrieval) by including CBVR (Content- Based Video Retrieval), which focused on the progress in last 3 years, and especially on video segmentation.

Publisher

IGI Global

Reference18 articles.

1. Parametric model for video content analysis

2. Visual categorization with bags of keypoints. In;G.Csurka;Proceedings of,2004

3. Dai, S. Y., & Zhang, Y. J. (2006). Color Image Segmentation in Both Feature andImage Spaces. In Y. Zhang, Advances in Image and Video Segmentation (pp. 209-227), Hershey, PA: IRM Press.

4. Object class recognition by unsupervised scale-invariant learning. In;R.Fergus;Proceedings of CVPR,2003

5. A survey on image segmentation

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Half Century for Image Segmentation;Encyclopedia of Information Science and Technology, Third Edition;2015

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