Journal
NEUROCOMPUTING
Volume 149, Issue -, Pages 736-751Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2014.08.003
Keywords
Visual feature detection; Machine learning; Edge detection; Corner detection; Blob detection
Categories
Funding
- National High Technology Research and Development Program of China (863 program) [2012AA011004]
- National Science and Technology Support Program [2013BAK02804]
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Feature detection is a fundamental and important problem in computer vision and image processing. It is a low-level processing step which serves as the essential part for computer vision based applications. The goal of this paper is to present a survey of recent progress and advances in visual feature detection. Firstly we describe the relations among edges, corners and blobs from the psychological view. Secondly we classify the algorithms in detecting edges, corners and blobs into different categories and provide detailed descriptions for representative recent algorithms in each category. Considering that machine learning becomes more involved in visual feature detection, we put more emphasis on machine learning based feature detection methods. Thirdly, evaluation standards and databases are also introduced. Through this survey we would like to present the recent progress in visual feature detection and identify future trends as well as challenges. (C) 2014 Elsevier B.V. All rights reserved.
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