Vision 2001: From A Different Angle, vol. 2

2001 Yearbook

La vision du monde dans la mythologie maseuale (nahua) de la Sierra Norte de Puebla (Mexique)

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Can aberrometry provide rapid and reliable measures of subjective depth of focus following multifocal intraocular lens implantation?

Purpose: To determine whether the ‘through-focus’ aberrations of a multifocal and accommodative intraocular lens (IOL) implanted patient can be used to provide rapid and reliable measures of their subjective range of clear vision. Methods: Eyes that had been implanted with a concentric (n = 8), segmented (n = 10) or accommodating (n = 6) intraocular lenses (mean age 62.9 ± 8.9 years; range 46-79 years) for over a year underwent simultaneous monocular subjective (electronic logMAR test chart at 4m with letters randomised between presentations) and objective (Aston open-field aberrometer) defocus curve testing for levels of defocus between +1.50 to -5.00DS in -0.50DS steps, in a randomised order. Pupil size and ocular aberration (a combination of the patient’s and the defocus inducing lens aberrations) at each level of blur was measured by the aberrometer. Visual acuity was measured subjectively at each level of defocus to determine the traditional defocus curve. Objective acuity was predicted using image quality metrics. Results: The range of clear focus differed between the three IOL types (F=15.506, P=0.001) as well as between subjective and objective defocus curves (F=6.685, p=0.049). There was no statistically significant difference between subjective and objective defocus curves in the segmented or concentric ring MIOL group (P>0.05). However a difference was found between the two measures and the accommodating IOL group (P<0.001). Mean Delta logMAR (predicted minus measured logMAR) across all target vergences was -0.06 ± 0.19 logMAR. Predicted logMAR defocus curves for the multifocal IOLs did not show a near vision addition peak, unlike the subjective measurement of visual acuity. However, there was a strong positive correlation between measured and predicted logMAR for all three IOLs (Pearson’s correlation: P<0.001). Conclusions: Current subjective procedures are lengthy and do not enable important additional measures such as defocus curves under differently luminance or contrast levels to be assessed, which may limit our understanding of MIOL performance in real-world conditions. In general objective aberrometry measures correlated well with the subjective assessment indicating the relative robustness of this technique in evaluating post-operative success with segmented and concentric ring MIOL.

Learning and Exploiting Camera Geometry for Computer Vision

This work explores the use of statistical methods in describing and estimating camera poses, as well as the information feedback loop between camera pose and object detection. Surging development in robotics and computer vision has pushed the need for algorithms that infer, understand, and utilize information about the position and orientation of the sensor platforms when observing and/or interacting with their environment.

The first contribution of this thesis is the development of a set of statistical tools for representing and estimating the uncertainty in object poses. A distribution for representing the joint uncertainty over multiple object positions and orientations is described, called the mirrored normal-Bingham distribution. This distribution generalizes both the normal distribution in Euclidean space, and the Bingham distribution on the unit hypersphere. It is shown to inherit many of the convenient properties of these special cases: it is the maximum-entropy distribution with fixed second moment, and there is a generalized Laplace approximation whose result is the mirrored normal-Bingham distribution. This distribution and approximation method are demonstrated by deriving the analytical approximation to the wrapped-normal distribution. Further, it is shown how these tools can be used to represent the uncertainty in the result of a bundle adjustment problem.

Another application of these methods is illustrated as part of a novel camera pose estimation algorithm based on object detections. The autocalibration task is formulated as a bundle adjustment problem using prior distributions over the 3D points to enforce the objects' structure and their relationship with the scene geometry. This framework is very flexible and enables the use of off-the-shelf computational tools to solve specialized autocalibration problems. Its performance is evaluated using a pedestrian detector to provide head and foot location observations, and it proves much faster and potentially more accurate than existing methods.

Finally, the information feedback loop between object detection and camera pose estimation is closed by utilizing camera pose information to improve object detection in scenarios with significant perspective warping. Methods are presented that allow the inverse perspective mapping traditionally applied to images to be applied instead to features computed from those images. For the special case of HOG-like features, which are used by many modern object detection systems, these methods are shown to provide substantial performance benefits over unadapted detectors while achieving real-time frame rates, orders of magnitude faster than comparable image warping methods.

The statistical tools and algorithms presented here are especially promising for mobile cameras, providing the ability to autocalibrate and adapt to the camera pose in real time. In addition, these methods have wide-ranging potential applications in diverse areas of computer vision, robotics, and imaging.

Reviewing March's vision

This paper reviews a remarkable experiment in organisation. At the centre of the story is James G. (Jim) March, one of the most influential scholars in management and organisation studies over the last half century. From 1954 to 1964, March was a leading member of the Graduate School of Administration (GSIA) at the Carnegie Institute of Technology, which was an extraordinary hotbed of ideas and research at that time. The group was led by Herbert Simon, a true polymath who is now recognised as a founding father of many scientific domains.

La vision du monde dans la mythologie maseuale (nahua) de la Sierra Norte de Puebla (Mexique)

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.