Abstract
Description of camera motion is one of the critical issues to implement automatic return for camera. This paper employs the Affine Transform Model to describe global motion, thus reconstructing movement of the camera according to information extracted from features of adjacent frames. Algorithm for feature point extraction is mainly discussed. In combination with secondary matching, SIFT (Scale Invariant Feature Transform) is improved by taking the density of points into consideration. The experimental results show that this method enhances the precision of matching with good real-time performance.
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Wang, Y. (2013). Research of Camera Track Based on Image Matching. In: Elleithy, K., Sobh, T. (eds) Innovations and Advances in Computer, Information, Systems Sciences, and Engineering. Lecture Notes in Electrical Engineering, vol 152. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3535-8_29
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DOI: https://doi.org/10.1007/978-1-4614-3535-8_29
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