Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77387
Title: VisFM : Visual analysis of image feature matchings
Authors: Li, C 
Baciu, G 
Keywords: Image processing
Information visualization
Visual analytics
Issue Date: 2018
Publisher: Wiley-Blackwell
Source: Computer graphics forum, 2018 How to cite?
Journal: Computer graphics forum 
Abstract: Feature matching is the most basic and pervasive problem in computer vision and it has become a primary component in big data analytics. Many tools have been developed for extracting and matching features in video streams and image frames. However, one of the most basic tools, that is, a tool for simply visualizing matched features for the comparison and evaluation of computer vision algorithms is not generally available, especially when dealing with a large number of matching lines. We introduce VisFM, an integrated visual analysis system for comprehending and exploring image feature matchings. VisFM presents a matching view with an intuitive line bundling to provide useful insights regarding the quality of matched features. VisFM is capable of showing a summarization of the features and matchings through group view to assist domain experts in observing the feature matching patterns from multiple perspectives. VisFM incorporates a series of interactions for exploring the feature data. We demonstrate the visual efficacy of VisFM by applying it to three scenarios. An informal expert feedback, conducted by our collaborator in computer vision, demonstrates how VisFM can be used for comparing and analysing feature matchings when the goal is to improve an image retrieval algorithm.
URI: http://hdl.handle.net/10397/77387
ISSN: 0167-7055
EISSN: 1467-8659
DOI: 10.1111/cgf.13391
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