Wide-Angle Foveation for All-Purpose Use

This paper proposes a model of a wide-angle space-variant image that provides a guide for designing a fovea sensor. First, an advanced wide-angle foveated (AdWAF) model is formulated, taking all-purpose use into account. This proposed model uses both Cartesian (linear) coordinates and logarithmic coordinates in both planar projection and spherical projection. Thus, this model divides its wide-angle field of view into four areas, such that it can represent an image by various types of lenses, flexibly. The first simulation compares with other lens models, in terms of image height and resolution. The result shows that the AdWAF model can reduce image data by 13.5%, compared to a log-polar lens model, both having the same resolution in the central field of view. The AdWAF image is remapped from an actual input image by the prototype fovea lens, a wide-angle foveated (WAF) lens, using the proposed model. The second simulation compares with other foveation models used for the existing log-polar chip and vision system. The third simulation estimates a scale-invariant property by comparing with the existing fovea lens and the log-polar lens. The AdWAF model gives its planar logarithmic part a complete scale-invariant property, while the fovea lens has 7.6% error at most in its spherical logarithmic part. The fourth simulation computes optical flow in order to examine the unidirectional property when the fovea sensor by the AdWAF model moves, compared to the pinhole camera. The result obtained by using a concept of a virtual cylindrical screen indicates that the proposed model has advantages in terms of computation and application of the optical flow when the fovea sensor moves forward

Eccentricity Compensator for Log-Polar Sensor

his paper aims at acquiring robust rotation, scale, and translation-invariant feature from a space-variant image by a fovea sensor. A proposed model of eccentricity compensator corrects deformation that occurs in a log-polar image when the fovea sensor is not centered at a target, that is, when eccentricity exists. An image simulator in discrete space remaps a compensated log-polar image using this model. This paper proposes unreliable feature omission (UFO) that reduces local high frequency noise in the space-variant image using discrete wavelet transform. It discards coefficients when they are regarded as unreliable based on digitized errors of the input image. The first simulation mainly tests geometric performance of the compensator, in case without noise. This result shows the compensator performs well and its root mean square error (RMSE) changes only by up to 2.54 [%] in condition of eccentricity within 34.08[deg]. The second simulation applies UFO to the log-polar image remapped by the compensator, taking its space-variant resolution into account. The result draws a conclusion that UFO performs better in case with more white Gaussian noise (WGN), even if the resolution of the compensated log-polar image is not isotropic

Object tracking using log-polar transformation

In this thesis, we use log-polar transform to solve object tracking. Object tracking in video sequences is a fundamental problem in computer vision. Even though object tracking is being studied extensively, still some challenges need to be addressed, such as appearance variations, large scale and rotation variations, and occlusion. We implemented a novel tracking algorithm which works robustly in the presence of large scale changes, rotation, occlusion, illumination changes, perspective transformations and some appearance changes. Log-polar transformation is used to achieve robustness to scale and rotation. Our object tracking approach is based on template matching technique. Template matching is based on extracting an example image, template, of an object in first frame, and then finding the region which best suites this template in the subsequent frames. In template matching, we implemented a fixed template algorithm and a template update algorithm. In the fixed template algorithm we use same template for the entire image sequence, where as in the template update algorithm the template is updated according to the changes in object image. The fixed template algorithm is faster; the template update algorithm is more robust to appearance changes in the object being tracked. The proposed object tracking is highly robust to scale, rotation, illumination changes and occlusion with good implementation speed

Foveated active tracking with redundant 2D motion parameters

This work presents a real-time active vision tracking system based on log-polar image motion estimation with 2D geometric deformation models. We present a very efficient parametric motion estimation method, where most computation can be done offline. We propose a redundant parameterization for the geometric deformations, which improve the convergence range of the algorithm. A foveated image representation provides extra computational savings and attenuation of background effects. A proper choice of motion models and a hierarchical organization of the iterations provide additional robustness. We present a fully integrated system with real-time performance and robustness to moderate deviations from the assumed deformation models. 2002 Elsevier Science B.V. All rights reserved