Application of Hierarchical Clustering for Object Tracking with a Dynamic Vision Sensor-Reference-Cited by-同舟云学术

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Application of Hierarchical Clustering for Object Tracking with a Dynamic Vision Sensor

Published:2019 Issue: Volume: Page:164-176
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Bolten Tobias,Pohle-Fröhlich Regina,Tönnies Klaus D.

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-22750-0_13

Reference18 articles.

1. Ranftl, A., Alonso-Fernandez, F., Karlsson, S.: Face tracking using optical flow. In: International Conference of the Biometrics Special Interest Group (BIOSIG), Darmstadt, pp. 1–5 (2015)

2. Liu, Y., Lu, Y., Shi, Q., Ding, J.: Optical flow based urban road vehicle tracking. In: Ninth International Conference on Computational Intelligence and Security, Leshan, pp. 391–395 (2013)

3. Dan, L., Dai-Hong, J., Rong, B., Jin-Ping, S., Wen-Jing, Z., Chao, W.: Moving object tracking method based on improved lucas-kanade sparse optical flow algorithm. In: International Smart Cities Conference (ISC2), Wuxi, pp. 1–5 (2017)

4. Bukey, C.M., Kulkarni, S.V., Chavan, R.A.: Multi-object tracking using Kalman filter and particle filter. In: IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), Chennai, pp. 1688–1692 (2017)

5. Mu, X., Che, J., Hu, T., Wang, Z.: A video object tracking algorithm combined Kalman filter and adaptive least squares under occlusion. In: 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), Datong, pp. 6–10 (2016)

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