Abstract
Feature matching is a basic process of many computer vision applications such as object detection or image stitching. A lot of state of the art technologies of feature extraction are focusing on the internal features of object. They perform great matching result but some of them spend extensive computational time to extract and match the features. In this paper, we propose a robust method for keypoint detection, description, and matching. The proposed algorithm is based on the point that people can recognize the object through the silhouette, firstly. We use object’s contour to extract their features. We can see that the proposed scheme can reduce much time to extract features through experiments.
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© 2015 Springer Science+Business Media Singapore
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Hu, W., Koo, Ms., Nam, JH., Kim, BG., Kim, SK. (2015). Robust Feature Design for Object Detection. In: Park, DS., Chao, HC., Jeong, YS., Park, J. (eds) Advances in Computer Science and Ubiquitous Computing. Lecture Notes in Electrical Engineering, vol 373. Springer, Singapore. https://doi.org/10.1007/978-981-10-0281-6_17
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DOI: https://doi.org/10.1007/978-981-10-0281-6_17
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