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Conference Paper Real-Time Panorama Image Stitching based on Multi-Threaded System
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Authors
Ahyun Lee, Insung Jang
Issue Date
2017-11
Citation
International Conference on Machine Learning and Data Engineering (iCMLDE) 2017, pp.1-6
Language
English
Type
Conference Paper
Abstract
This paper proposes a user-friendly panorama image stitching system with a real-time preview. Previous approaches do not have a choice but to the select source images while the user predicts the stitching results through trial and error. Our contribution shows a real-time preview of the stitching results based on the multi-threaded tracking and the blending system. It can help the user easily generate a desired panorama image such as a wide-angle view or building. In our system, the object image designated as an initial frame is tracked to generate a real-time preview. We evaluated the accuracy of the proposed tracking method as compared with a scale-invariant feature transform, such as speededup robust features, and oriented FAST, rotated BRIEF. Our experiment results show that our approach can robustly track the object image and provide quality real-time preview images.
KSP Keywords
Blending system, Experiment results, Multi-threaded, Object image, Panorama image, Real-time, Robust feature, Tracking method, User-friendly, image stitching, scale invariant feature transform(SIFT)