The role of convexity in the corner enhancement effect, in visual short- term memory, in perception of symmetry, and in shape interference.

Contour curvature information has been shown to have an impact on the visual perception of shape. We have conducted studies on perception of convexity and concavity in relation to memory and attention. Previous studies (Badcock & Westheirner, 1985; Krose & Julesz, 1989; Nakayama & Mackeben, 1989) have proposed that visual space is influenced by corners. Recent studies by Cole, Burton and Gellatly (2001) found that reaction times were faster for a stimulus located in the region of a corner of a figure. Cole et al (2001) believe that the role of corners is greater than that of straight edges, due to corners receiving a higher distribution of attentional resources relative to straight edges. The first part of this thesis considers the role figure-ground plays in the corner enhancement effect. Results demonstrate that the corner enhancement effect is only found when the probe is presented on the surface that owns the corner. Thus the corner enhancement effect is present for both concave and convex vertices. However, the effect disappears when the probe lay on the surface that does not own the corner. The second series of experiments made use of a shape with multiple concave or convex features as part of a change detection task, in which only a single feature could change. The results provided no evidence to suggest that convexities are special in visual short-term memory. Though coding of convexities as well as concavities provided a small advantage over an isolated contour. This finding is in accordance with the well documented effect of closure on shape processing (Elder & Zucker, 1993). It has been reported that deviations from symmetry were easier to detect when carried by convexities compared to deviations carried by concavities (Hulleman & Olivers, 2007). We extended this investigation to shapes that were repeated instead of reflected, to test whether there is a specific convexity advantage for bilateral symmetry. The results supported a convexity advantage for repetitions but not for reflections. Possible explanations for this are discussed. The final series of experiments involved a shape interference task; observers responded to circles or square in the context of irrelevant circles and squares. The findings suggest that interference between the shapes is much stronger when the contours that define the shapes belong to the same surface. In summary, we conclude that convexity and concavity are important aspects of shape analysis and representation, but there is no basic difference in how convexities and concavities are attended to, both in the corner enhancement effect, and in visual-short term memory. However, convexity plays a role in some perceptual tasks for example, when analyzing complex shapes observers may adopt strategies that focus on the convexities

Computational Models of Perceptual Organization and Bottom-up Attention in Visual and Audio-Visual Environments

Figure Ground Organization (FGO) - inferring spatial depth ordering of objects in a visual scene - involves determining which side of an occlusion boundary (OB) is figure (closer to the observer) and which is ground (further away from the observer). Attention, the process that governs how only some part of sensory information is selected for further analysis based on behavioral relevance, can be exogenous, driven by stimulus properties such as an abrupt sound or a bright flash, the processing of which is purely bottom-up; or endogenous (goal-driven or voluntary), where top-down factors such as familiarity, aesthetic quality, etc., determine attentional selection. The two main objectives of this thesis are developing computational models of: (i) FGO in visual environments; (ii) bottom-up attention in audio-visual environments. In the visual domain, we first identify Spectral Anisotropy (SA), characterized by anisotropic distribution of oriented high frequency spectral power on the figure side and lack of it on the ground side, as a novel FGO cue, that can determine Figure/Ground (FG) relations at an OB with an accuracy exceeding 60%. Next, we show a non-linear Support Vector Machine based classifier trained on the SA features achieves an accuracy close to 70% in determining FG relations, the highest for a stand-alone local cue. We then show SA can be computed in a biologically plausible manner by pooling the Complex cell responses of different scales in a specific orientation, which also achieves an accuracy greater than or equal to 60% in determining FG relations. Next, we present a biologically motivated, feed forward model of FGO incorporating convexity, surroundedness, parallelism as global cues and SA, T-junctions as local cues, where SA is computed in a biologically plausible manner. Each local cue, when added alone, gives statistically significant improvement in the model's performance. The model with both local cues achieves higher accuracy than those of models with individual cues in determining FG relations, indicating SA and T-Junctions are not mutually contradictory. Compared to the model with no local cues, the model with both local cues achieves greater than or equal to 8.78% improvement in determining FG relations at every border location of images in the BSDS dataset. In the audio-visual domain, first we build a simple computational model to explain how visual search can be aided by providing concurrent, co-spatial auditory cues. Our model shows that adding a co-spatial, concurrent auditory cue can enhance the saliency of a weakly visible target among prominent visual distractors, the behavioral effect of which could be faster reaction time and/or better search accuracy. Lastly, a bottom-up, feed-forward, proto-object based audiovisual saliency map (AVSM) for the analysis of dynamic natural scenes is presented. We demonstrate that the performance of proto-object based AVSM in detecting and localizing salient objects/events is in agreement with human judgment. In addition, we show the AVSM computed as a linear combination of visual and auditory feature conspicuity maps captures a higher number of valid salient events compared to unisensory saliency maps

Eliciting Perceptual Ground Truth for Image Segmentation

In this paper, we investigate human visual perception and establish a body of ground truth data elicited from human visual studies. We aim to build on the formative work of Ren, Eakins and Briggs who produced an initial ground truth database. Human subjects were asked to draw and rank their perceptions of the parts of a series of figurative images. These rankings were then used to score the perceptions, identify the preferred human breakdowns and thus allow us to induce perceptual rules for human decomposition of figurative images. The results suggest that the human breakdowns follow well-known perceptual principles in particular the Gestalt laws

Monocular Depth Ordering Using Occlusion Cues

English: This project proposes a system to relate the objects in an image using occlusion cues and arrange them according to depth. The system does not rely on a priori knowledge of the scene structure and focus on detecting special points, such as T-junctions and high convexity regions, to infer the depth relationships between objects in the scene. The system makes extensive use of the Binary Partition Tree (BPT) as the segmentation tool jointly with a new approach for T-junction candidate point estimation. In a BPT approach, as a bottom-up strategy, regions are iteratively merged and grown from pixels until only one region is left. At each step, our system estimates the junction points, where three regions meet. When the BPT is constructed and the pruning is performed, this information is used for depth ordering. Since many images may not have occlusion points formed by junctions, occlusion is also detected by examining convex shapes on region boundaries. Combining T-junctions and convexity lead to a system which only relies on low level depth cues and does not involve any learning process. However, it shows a similar performance with the state of the art

Neural models of inter-cortical networks in the primate visual system for navigation, attention, path perception, and static and kinetic figure-ground perception

Vision provides the primary means by which many animals distinguish foreground objects from their background and coordinate locomotion through complex environments. The present thesis focuses on mechanisms within the visual system that afford figure-ground segregation and self-motion perception. These processes are modeled as emergent outcomes of dynamical interactions among neural populations in several brain areas. This dissertation specifies and simulates how border-ownership signals emerge in cortex, and how the medial superior temporal area (MSTd) represents path of travel and heading, in the presence of independently moving objects (IMOs). Neurons in visual cortex that signal border-ownership, the perception that a border belongs to a figure and not its background, have been identified but the underlying mechanisms have been unclear. A model is presented that demonstrates that inter-areal interactions across model visual areas V1-V2-V4 afford border-ownership signals similar to those reported in electrophysiology for visual displays containing figures defined by luminance contrast. Competition between model neurons with different receptive field sizes is crucial for reconciling the occlusion of one object by another. The model is extended to determine border-ownership when object borders are kinetically-defined, and to detect the location and size of shapes, despite the curvature of their boundary contours. Navigation in the real world requires humans to travel along curved paths. Many perceptual models have been proposed that focus on heading, which specifies the direction of travel along straight paths, but not on path curvature. In primates, MSTd has been implicated in heading perception. A model of V1, medial temporal area (MT), and MSTd is developed herein that demonstrates how MSTd neurons can simultaneously encode path curvature and heading. Human judgments of heading are accurate in rigid environments, but are biased in the presence of IMOs. The model presented here explains the bias through recurrent connectivity in MSTd and avoids the use of differential motion detectors which, although used in existing models to discount the motion of an IMO relative to its background, is not biologically plausible. Reported modulation of the MSTd population due to attention is explained through competitive dynamics between subpopulations responding to bottom-up and top- down signals

Gestalt Theory and Its Reception: An Annotated Bibliography

The list which follows is intended as a comprehensive bibliographical survey of the wider Gestalt tradition from Graz and Berlin to Padua, Frankfurt and New York. It presents diagrammatically the main influence and teacher-pupil relationships also groupings into schools. It includes the classical texts of the Gestalt psychological tradition, together with the more important translations and reprints thereof. Special attention is paid to works on the following topics: - the concept of Prägnanz or `good form' and related treatments of aesthetic phenomena and of pattern recognition - cognitive processes and problem-solving - criticisms of Gestalt theoru - phenomenal causation - figure-ground relations , phenomenaI boundaries, subjective contours - phenomenal motion - perceptual constancies - philosophical inquiries into the nature of `configuration'. `relation', `structure', etc . , and writing on psychological holism (but only insofar as they relate directly to the literature of Gestalt psychology proper

Engineering data compendium. Human perception and performance. User's guide

The concept underlying the Engineering Data Compendium was the product of a research and development program (Integrated Perceptual Information for Designers project) aimed at facilitating the application of basic research findings in human performance to the design and military crew systems. The principal objective was to develop a workable strategy for: (1) identifying and distilling information of potential value to system design from the existing research literature, and (2) presenting this technical information in a way that would aid its accessibility, interpretability, and applicability by systems designers. The present four volumes of the Engineering Data Compendium represent the first implementation of this strategy. This is the first volume, the User's Guide, containing a description of the program and instructions for its use

Visual recognition of objects : behavioral, computational, and neurobiological aspects

I surveyed work on visual object recognition and perception. In animals, vision has been studied mainly on the behavioral and neurobiological levels. Behavioral data typically show what the visual system, by itself or together with the rest of the organism, is capable of. They show, for example, that humans can recognie objects regardless of size and position, but that rotated objects pose problems. Important insights into the organization of behavior have also been provided by people who suffered localized brain damage. We have learned that the brain is divided into areas subserving different and relatively well-defined behaviors. The visual system itself is also organized in different subsystems; the visual cortex alone contains nearly twenty maps of the visual field. And individual neurons respond selectively to visual stimuli, e.g., the orientation of line segments, color, direction of motion, and, most intriguingly, faces. The question is how the actions of all these neurons produce the behavior we observe. How do neurons represent the shape of objects such that they can be recognized? Before we can answer the question, we have to understand the computational aspect of shape representation, the nature of the problem as it were. Many methods for representing shape have been explored, mainly by computer scientists, but so far no satisfactory answers have been found