Open Access
| Issue |
MATEC Web Conf.
Volume 95, 2017
2016 the 3rd International Conference on Mechatronics and Mechanical Engineering (ICMME 2016)
|
|
|---|---|---|
| Article Number | 08013 | |
| Number of page(s) | 5 | |
| Section | Robot Design and Control | |
| DOI | https://doi.org/10.1051/matecconf/20179508013 | |
| Published online | 09 February 2017 | |
- L. Li, W. Huang, Y.H. Gu, Q. Tian, “Statistical Modeling of Complex Backgrounds for Foreground Object Detection” IEEE TRANSACTIONS ON IMAGE PROCESSING, 13, 1459–1472 (2004). [CrossRef] [Google Scholar]
- S. Denman, V. Chandran, S. Sridharan, “An adaptive optical flow technique for person tracking systems” Pattern Recogn, 28, 1232–1239 (2007). [CrossRef] [Google Scholar]
- W. H. Warren, D. J. Hannon, “Direction of self-motion is perceived from optical flow” Nature, 336, 162–163 (1988). [CrossRef] [Google Scholar]
- S. Baker, D. Scharstein, J.P. Lewis, S. Roth, M. J. Black, R. Szeliski, “A Database and Evaluation Methodology for Optical Flow” INT J COMPUT VISION, 92, 1–31 (2007). [CrossRef] [Google Scholar]
- D. Decarlo, D. Metaxas, “The Integration of Optical Flow and Deformable Models with Applications to Human Face Shape and Motion Estimation” Conference on Computer Vision and Pattern Recognition (San Francisco, CA, USA, 1996). [Google Scholar]
- D. Honegger, L. Meier, P. Tanskanen, M. Pollefeys, “An Open Source and Open Hardware Embedded Metric Optical Flow CMOS Camera for Indoor and Outdoor Applications” IEEE International Conference on Robotics and Automation (Karlsruhe, Germany, 2013). [Google Scholar]
- K. Steinkraus, L. P. Kaelbling, “Optical Flow for Obstacle Detection in Mobile Robots” Artificial Intelligence Laboratory Mit (2001). [Google Scholar]
- Y. P. Tan, S. R. Kulkarni, P. J. Ramadge, “A New Method for Camera Motion Parameter Estimation” International Conference on Image Processing, 1, 406 (1995). [CrossRef] [Google Scholar]
- N. Johansson, F. Williamsson, “Human Machine Interface Visualization Enhancement of an ABB Quality Control System” Umea University Department of Computing Science (2009). [Google Scholar]
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