A Quantitative Comparison of Speed and Reliability for Log-Polar Mapping Techniques

A space-variant representation of images is of great importance for active vision systems capable of interacting with the environment. A precise processing of the visual signal is achieved in the fovea, and, at the same time, a coarse computation in the periphery provides enough information to detect new saliences on which to bring the focus of attention. In this work, different techniques to implement the blind-spot model for the log-polar mapping are quantitatively analyzed to assess the visual quality of the transformed images and to evaluate the associated computational load. The technique with the best trade-off between these two aspects is expected to show the most efficient behaviour in robotic vision systems, where the execution time and the reliability of the visual information are crucial.

[1]  Alexandre Bernardino,et al.  Visual behaviours for binocular tracking , 1998, Robotics Auton. Syst..

[2]  Filiberto Pla,et al.  Log-polar mapping template design: From task-level requirements to geometry parameters , 2008, Image Vis. Comput..

[3]  Alexandre Bernardino,et al.  A Binocular Stereo Algorithm for Log-Polar Foveated Systems , 2002, Biologically Motivated Computer Vision.

[4]  Giulio Sandini,et al.  Anthropomorphic Visual Sensors , 2005 .

[5]  Seong-Whan Lee,et al.  Biologically Motivated Computer Vision , 2002, Lecture Notes in Computer Science.

[6]  Yiannis Aloimonos,et al.  Active vision , 2004, International Journal of Computer Vision.

[7]  Y. Mohammed.  Optical flow in log-mapped image plane - a new approach , 2002 .

[8]  Mohammed Yeasin,et al.  Optical Flow in Log-Mapped Image Plane-A New Approach , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Alan C. Bovik,et al.  Image information and visual quality , 2006, IEEE Trans. Image Process..

[10]  Fabrizio Smeraldi,et al.  Retinal vision applied to facial features detection and face authentication , 2002, Pattern Recognit. Lett..

[11]  E. L. Schwartz,et al.  Spatial mapping in the primate sensory projection: Analytic structure and relevance to perception , 1977, Biological Cybernetics.

[12]  Frédéric Jurie,et al.  A new log-polar mapping for space variant imaging.: Application to face detection and tracking , 1999, Pattern Recognit..

[13]  Alexandre Bernardino,et al.  A review of log-polar imaging for visual perception in robotics , 2010, Robotics and Autonomous Systems.

[14]  Paul S. Fisher,et al.  Image quality measures and their performance , 1995, IEEE Trans. Commun..

[15]  Hamid R. Rabiee,et al.  A novel rotation/scale invariant template matching algorithm using weighted adaptive lifting scheme transform , 2010, Pattern Recognit..

[16]  Alexandre Bernardino,et al.  Smooth Foveal vision with Gaussian receptive fields , 2009, 2009 9th IEEE-RAS International Conference on Humanoid Robots.

[17]  David S. Young.  Straight Lines and Circles in the Log-Polar Image , 2000, BMVC.

[18]  Giulio Sandini,et al.  Foveated active tracking with redundant 2D motion parameters , 2002, Robotics Auton. Syst..

[19]  Alan C. Bovik,et al.  Image quality assessment using natural scene statistics , 2004 .

[20]  Martin D. Levine,et al.  A Real-Time Foveated Sensor with Overlapping Receptive Fields , 1997, Real Time Imaging.

[21]  Xuejie Zhang,et al.  A spatial variant approach for vergence control in complex scenes , 2011, Image Vis. Comput..

[22]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.