Space Variant Representations for Mobile Platform Vision Applications
作者： Naveen Onkarappa , Angel D. Sappa
DOI: 10.1007/978-3-642-23678-5_16
关键词:
摘要: The log-polar space variant representation, motivated by biological vision, has been widely studied in the literature. Its data reduction and invariance properties made it useful many vision applications. However, due to its nature, fails preserving features periphery. In current work, as an attempt overcome this problem, we propose a novel space-variant representation. It is evaluated proved be better than representation peripheral information, crucial for on-board mobile evaluation performed comparing proposed once they are used estimating dense optical flow.
springer.com
uab.es 
sci-hub.st 参考文章(18)
Konstantinos Daniilidis, Volker Krüger, Optical Flow Computation in the Log-Polar-Plane computer analysis of images and patterns. pp. 65- 72 ,(1995) , 10.1007/3-540-60268-2_281
V. Javier Traver, Filiberto Pla, The Log-polar Image Representation in Pattern Recognition Tasks iberian conference on pattern recognition and image analysis. pp. 1032- 1040 ,(2003) , 10.1007/978-3-540-44871-6_119
C. Zach, T. Pock, H. Bischof, A duality based approach for realtime TV-L 1 optical flow dagm conference on pattern recognition. pp. 214- 223 ,(2007) , 10.1007/978-3-540-74936-3_22
Image Analysis and Recognition Lecture Notes in Computer Science. ,vol. 5627, ,(2004) , 10.1007/978-3-319-11755-3
Naveen Onkarappa, Angel D. Sappa, On-Board Monocular Vision System Pose Estimation through a Dense Optical Flow Lecture Notes in Computer Science. ,vol. 2010, pp. 230- 239 ,(2010) , 10.1007/978-3-642-13772-3_24
Y. Mohammed, Optical flow in log-mapped image plane - a new approach IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 24, pp. 125- 131 ,(2002) , 10.1109/34.982889
Eric L. Schwartz, Douglas N. Greve, Giorgio Bonmassar, Space-variant active vision: definition, overview and examples Neural Networks. ,vol. 8, pp. 1297- 1308 ,(1995) , 10.1016/0893-6080(95)00092-5
Deqing Sun, Stefan Roth, Michael J. Black, Secrets of optical flow estimation and their principles computer vision and pattern recognition. pp. 2432- 2439 ,(2010) , 10.1109/CVPR.2010.5539939
Simon Baker, Stefan Roth, Daniel Scharstein, Michael J. Black, J.P. Lewis, Richard Szeliski, A Database and Evaluation Methodology for Optical Flow international conference on computer vision. pp. 1- 8 ,(2007) , 10.1109/ICCV.2007.4408903
Marc Bolduc, Martin D. Levine, A review of biologically motivated space-variant data reduction models for robotic vision Computer Vision and Image Understanding. ,vol. 69, pp. 170- 184 ,(1998) , 10.1006/CVIU.1997.0560