Perception of physical stability and center of mass of 3-D objects

Humans can judge from vision alone whether an object is physically stable or not. Such judgments allow observers to predict the physical behavior of objects, and hence to guide their motor actions. We investigated the visual estimation of physical stability of 3-D objects (shown in stereoscopically viewed rendered scenes) and how it relates to visual estimates of their center of mass (COM). In Experiment 1, observers viewed an object near the edge of a table and adjusted its tilt to the perceived critical angle, i.e., the tilt angle at which the object was seen as equally likely to fall or return to its upright stable position. In Experiment 2, observers visually localized the COM of the same set of objects. In both experiments, observers´ settings were compared to physical predictions based on the objects´ geometry. In both tasks, deviations from physical predictions were, on average, relatively small. More detailed analyses of individual observers´ settings in the two tasks, however, revealed mutual inconsistencies between observers´ critical-angle and COM settings. The results suggest that observers did not use their COM estimates in a physically correct manner when making visual judgments of physical stability

Creating correct aberrations: why blur isn’t always bad in the eye

In optics in general, a sharp aberration-free image is normally the desired goal, and the whole field of adaptive optics has developed with the aim of producing blur-free images. Likewise, in ophthalmic optics we normally aim for a sharp image on the retina. But even with an emmetropic, or well-corrected eye, chromatic and high order aberrations affect the image. We describe two different areas where it is important to take these effects into account and why creating blur correctly via rendering can be advantageous. Firstly we show how rendering chromatic aberration correctly can drive accommodation in the eye and secondly report on matching defocus-l generated using rendering with conventional optical defocus

ChromaBlur: Rendering Chromatic Eye Aberration Improves Accommodation and Realism

Computer-graphics engineers and vision scientists want to generate images that reproduce realistic depth-dependent blur. Current rendering algorithms take into account scene geometry, aperture size, and focal distance, and they produce photorealistic imagery as with a high-quality camera. But to create immersive experiences, rendering algorithms should aim instead for perceptual realism. In so doing, they should take into account the significant optical aberrations of the human eye. We developed a method that, by incorporating some of those aberrations, yields displayed images that produce retinal images much closer to the ones that occur in natural viewing. In particular, we create displayed images taking the eye's chromatic aberration into account. This produces different chromatic effects in the retinal image for objects farther or nearer than current focus. We call the method ChromaBlur. We conducted two experiments that illustrate the benefits of ChromaBlur. One showed that accommodation (eye focusing) is driven quite effectively when ChromaBlur is used and that accommodation is not driven at all when conventional methods are used. The second showed that perceived depth and realism are greater with imagery created by ChromaBlur than in imagery created conventionally. ChromaBlur can be coupled with focus-adjustable lenses and gaze tracking to reproduce the natural relationship between accommodation and blur in HMDs and other immersive devices. It may thereby minimize the adverse effects of vergence-accommodation conflicts

Modeling Accommodation Control of the Human Eye: Chromatic Aberration and Color Opponency

Accommodation is the process by which the eye lens changes optical power to maintain a clear retinal image as the distance to the fixated object varies. Although luminance blur has long been considered the driving feature for accommodation, it is by definition unsigned (i.e., there is no difference between the defocus of an object closer or farther than the focus distance). Nonetheless, the visual system initially accommodates in the correct direction, implying that it exploits a cue with sign information. Here, we present a model of accommodation control based on such a cue: Longitudinal Chromatic Aberration (LCA). The model relies on color-opponent units, much like those observed among retinal ganglion cells, to make the computation required to use LCA to drive accommodation

The tipping point: visual estimation of the physical stability of three-dimensional objects

Vision research generally focuses on the currently visible surface properties of objects, such as color, texture, luminance, orientation, and shape. In addition, however, observers can also visually predict the physical behavior of objects, which often requires inferring the action of hidden forces, such as gravity and support relations. One of the main conclusions from the naive physics literature is that people often have inaccurate physical intuitions; however, more recent research has shown that with dynamic simulated displays, observers can correctly infer physical forces (e.g., timing hand movements to catch a falling ball correctly takes into account Newton’s laws of motion). One ecologically important judgment about physical objects is whether they are physically stable or not. This research project examines how people perceive physical stability and addresses (1) How do visual estimates of stability compare to physical predictions? Can observers track the influence of specific shape manipulations on object stability? (2) Can observers match stability across objects with different shapes? How is the overall stability of an object estimated? (3) Are visual estimates of object stability subject to adaptation effects? Is stability a perceptual variable? The experimental findings indicate that: (1) Observers are able to judge the stability of objects quite well and are close to the physical predictions on average. They can track how changing a shape will affect the physical stability; however, the perceptual influence is slightly smaller than physically predicted. (2) Observers can match the stabilities of objects with different three-dimensional shapes -- suggesting that object stability is a unitary dimension -- and their judgments of overall stability are strongly biased towards the minimum critical angle. (3) The majority of observers exhibited a stability adaptation aftereffect, providing evidence in support of the claim that stability may be a perceptual variable.Ph. D.Includes bibliographical referencesby Steven A. Cholewia

Perceptual estimation of variance in orientation and its dependence on sample size

Recent research has shown that participants are very good at perceptually estimating summary statistics of sets of similar objects (e.g., Ariely, 2001; Chong & Treisman, 2003; 2005). While the research has focused on first-order statistics (e.g., the mean size of a set of discs), it is unlikely that a mental representation of the world includes only a list of mean estimates (or expected values) of various attributes. Therefore, a comprehensive theory of perceptual summary statistics would be incomplete without an investigation of the representation of second-order statistics (i.e., variance). Two experiments were conducted to test participants' ability to discriminate samples that differed in orientation variability. Discrimination thresholds and points of subjective equality for displays of oriented triangles were measured in Experiment 1. The results indicated that participants could discriminate variance without bias and that participant sensitivity (measured via relative thresholds, i.e., Weber fractions) was dependent upon sample size but not baseline variance. Experiment 2 investigated whether participants used a simpler second-order statistic, namely, sample range to discriminate dispersion in orientation. The results of Experiment 2 showed that variance was a much better predictor of performance than sample range. Taken together, the experiments suggest that variance information is part of the visual system's representation of scene variables. However, unlike the estimation of first-order statistics, the estimation of variance depends crucially on sample size.M.S.Includes abstractIncludes bibliographical referencesby Steven A. Cholewia

Appearance Controls Interpretation of Orientation Flows for 3D Shape Estimation

The visual system can infer 3D shape from orientation flows arising from both texture and shading patterns. However, these two types of flows provide fundamentally different information about surface structure. Texture flows, when derived from distinct elements, mainly signal first-order features (surface slant), whereas shading flow orientations primarily relate to second-order surface properties (the change in surface slant). The source of an image\u27s structure is inherently ambiguous, it is therefore crucial for the brain to identify whether flow patterns originate from texture or shading to correctly infer shape from a 2D image. One possible approach would be to use \u27surface appearance\u27 (e.g. smooth gradients vs. fine-scale texture) to distinguish texture from shading. However, the structure of the flow fields themselves may indicate whether a given flow is more likely due to first- or second-order shape information. We test these two possibilities in this set of experiments, looking at speeded and free responses

Creating correct blur and its effect on accommodation

Blur occurs naturally when the eye is focused at one distance and an object is presented at another distance. Computer-graphics engineers and vision scientists often wish to create display images that reproduce such depth-dependent blur, but their methods are incorrect for that purpose. They take into account the scene geometry, pupil size, and focal distances, but do not properly take into account the optical aberrations of the human eye. We developed a method that, by incorporating the viewer’s optics, yields displayed images that produce retinal images close to the ones that occur in natural viewing. We concentrated on the effects of defocus, chromatic aberration, astigmatism, and spherical aberration and evaluated their effectiveness by conducting experiments in which we attempted to drive the eye’s focusing response (accommodation) through the rendering of these aberrations. We found that accommodation is not driven at all by conventional rendering methods, but that it is driven surprisingly quickly and accurately by our method with defocus and chromatic aberration incorporated. We found some effect of astigmatism but none of spherical aberration. We discuss how the rendering approach can be used in vision science experiments and in the development of ophthalmic/optometric devices and augmented- and virtual-reality displays