Moving Object Detection Algorithm Using Gaussian Mixture Model and SIFT Keypoint Match-Reference-Cited by-同舟云学术

Moving Object Detection Algorithm Using Gaussian Mixture Model and SIFT Keypoint Match

Published:2018 Issue: Volume: Page:22-29
ISSN:1867-8211
Container-title:Machine Learning and Intelligent Communications
language:
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Author:

Dong Hang,Zhang Xin

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-73564-1_3

Reference8 articles.

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3. Stauffer, C., Grimson, W.E.L.: Adaptive background mixture models for real-time tracking. In: IEEE Computer Society Conference on Computer Vision and Pattern Detection, vol. 2, pp. 246–252. IEEE Xplore (1999)

4. KaewTraKulPong, P., Bowden, R.: An improved adaptive background mixture model for real-time tracking with shadow detection. In: Remagnino, P., Jones, G.A., Paragios, N., Regazzoni, C.S. (eds.) Video-Based Surveillance Systems, pp. 135–144. Springer, Boston (2002). https://doi.org/10.1007/978-1-4615-0913-4_11

5. Lowe, D.G.: Distinctive Image Features from Scale-Invariant Keypoints. Kluwer Academic Publishers, Dordrecht (2004)

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