Inherent Ambiguities in Recovering 3-D Motion and Structure from a Noisy Flow Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Elements of information theory
Elements of information theory
Performance of optical flow techniques
International Journal of Computer Vision
Space variant image processing
International Journal of Computer Vision
First order optic flow from log-polar sampled images
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Space-variant active vision: definition, overview and examples
Neural Networks - Special issue: automatic target recognition
Optical normal flow estimation on log-polar images. A solution for real-time binocular vision
Real-Time Imaging - Special issue on natural and artificial real-time imaging and vision
A review of biologically motivated space-variant data reduction models for robotic vision
Computer Vision and Image Understanding
Ambiguity in Structure from Motion: Sphere versus Plane
International Journal of Computer Vision
Rapid Anisotropic Diffusion Using Space-Variant Vision
International Journal of Computer Vision
Optical Flow in Log-Mapped Image Plane-A New Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Optical Flow Computation in the Log-Polar-Plane
CAIP '95 Proceedings of the 6th International Conference on Computer Analysis of Images and Patterns
Computation of 3-D-Motion Parameters Using the Log-Polar Transform
CAIP '95 Proceedings of the 6th International Conference on Computer Analysis of Images and Patterns
Detecting Motion Independent of the Camera Movement Through a Log-Polar Differential Approach
CAIP '97 Proceedings of the 7th International Conference on Computer Analysis of Images and Patterns
Comparison of Approaches to Egomotion Computation
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
On the Spatial Statistics of Optical Flow
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Motion Analysis with the Radon Transform on Log-Polar Images
Journal of Mathematical Imaging and Vision
Efficient active monocular fixation using the log-polar sensor
International Journal of Intelligent Systems Technologies and Applications
A review of log-polar imaging for visual perception in robotics
Robotics and Autonomous Systems
A duality based approach for realtime TV-L1 optical flow
Proceedings of the 29th DAGM conference on Pattern recognition
On-Board monocular vision system pose estimation through a dense optical flow
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part I
A polar representation of motion and implications for optical flow
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
A continuative variable resolution digital elevation model for ground-based photogrammetry
Computers & Geosciences
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Traditionally, in machine vision images are represented using cartesian coordinates with uniform sampling along the axes. On the contrary, biological vision systems represent images using polar coordinates with non-uniform sampling. For various advantages provided by space-variant representations many researchers are interested in space-variant computer vision. In this direction the current work proposes a novel and simple space variant representation of images. The proposed representation is compared with the classical log-polar mapping. The log-polar representation is motivated by biological vision having the characteristic of higher resolution at the fovea and reduced resolution at the periphery. On the contrary to the log-polar, the proposed new representation has higher resolution at the periphery and lower resolution at the fovea. Our proposal is proved to be a better representation in navigational scenarios such as driver assistance systems and robotics. The experimental results involve analysis of optical flow fields computed on both proposed and log-polar representations. Additionally, an egomotion estimation application is also shown as an illustrative example. The experimental analysis comprises results from synthetic as well as real sequences.