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The visual system performs remarkably well to perceive depth order of surfaces without stereo disparity, indicating the importance of figure-ground organization based on pictorial cues. To understand how figure-ground organization emerges, it is essential to investigate how the global configuration of an image is reflected. In the past, many neuro-computational models developed to reproduce figure-ground organization implemented algorithms to give a bias to convex areas. However, in certain conditions, a convex area can be perceived as a hole and a nonconvex area as figural. This occurs when the surface properties of the convex area are consistent with the background and, hence, are grouped together in our perception. We argue that large-scale consistency of surface properties is reflected in the border-ownership computation. We developed a model, called DISC2, that first analyzes relationships between two border-ownership signals of all possible combinations in the image. It then enhances signals if they satisfy the following conditions: (a) the two signals fit to a convex configuration and (b) the surface properties at the locations of the two signals are consistent. The strength of the enhancement decays with distance between the signals. The model gives extremely robust responses to various images with complexities both in shape and depth order. Furthermore, we developed an advanced version of the model ("augmented model") where the global computation above interacts with local computation of curvilinearity, which further enhanced the robust nature of the model. The results suggest the involvement of similar computational processes in the brain for figure-ground organization. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Conventional accounts of motion perception mostly treat accretion/deletion-the appearance or disappearance of texture at a boundary between regions-as an essentially decisive cue to relative depth: the accreting/deleting surface is interpreted as being behind adjacent surfaces. Under certain circumstances, however, accretion/deletion can be perceived in a radically different way: the accreting or deleting surface is seen as rotating in depth in front of adjacent surfaces. This alternative interpretation suggests a problem in conventional accounts of motion interpretation that cannot account for this phenomenon, in part because they ignore the role of contour geometry. In two experiments, we examined the combined role of contour convexity and accretion/deletion in determining the perception of relative depth by parametrically manipulating the strength of each cue. Our results show that convexity plays a more substantial role, often dominating the 3D percept, even in cases when the saliency of the convexity cue is substantially weakened on a contour where the texture was accreting/deleting at high rates. These results highlight the need for a rethinking of theories of perceptual organization in the critical case of moving stimuli.

In this demo, we showcase the ``Talking to your Data'' system. The key idea of this system is to support data governance and data mining in a novel way. We aim to bring the use of interpretable machine learning techniques closer to the business analysts by using natural language. We have developed a conversational agent and a data mining backend that supports the analysis of data. Our approach facilitates solving prediction tasks and also provides explanations for these predictions. Furthermore, we make possible the interaction for including the feedback of the business analysts in the models.

In this master thesis, a new interactive subgroup discovery algorithm is proposed. This method has two main contributions. First, the algorithm allows the expert to intervene during the search process by assessing each subgroup with a degree of appreciation which influences the search process. The second contribution is a diversity parameter that allows the user to avoid that the new subgroups share more than a chosen percentage of instances with already found subgroups. Experiments show that when diversity control is performed, the resulting subgroups have less overlap than the baseline version of the algorithm. Additionally, when using the proposed interactive version of the algorithm, a higher user appreciation of the subgroups is observed. This interactive subgroup discovery algorithm was implemented in the backend of a conversational agent for supporting business analysts in data mining tasks.

Standard accounts of accretion/deletion of texture treat it as a definite cue to depth ordering: The accreting/deleting surface is interpreted as being behind the adjoining surface. Froyen, Feldman, and Singh showed that accretion/deletion can also, under certain circumstances, be perceived as a 3D column rotating in front, with the accretion/deletion explained by self-occlusion. These displays differ from traditional accretion/deletion displays in a number of factors, including the presence of figure/ground cues, accretion/deletion on both sides of boundaries, and in the number of distinct regions. In a series of experiments, we systematically manipulated each of these factors in order to determine what factors are actually instrumental in creating the rotating column (accretion/deletion in front) interpretation. In Experiment 1, the width of each region was kept fixed while manipulating the number of regions, and in Experiment 2, the width of the overall display was kept fixed. Observers indicated which set of regions they perceived to be in front. In both experiments, accreting/deleting regions were most likely to be seen in front when geometric figural cues favored a figural interpretation and when textural motion was introduced in all regions (rather than on just one side of each boundary). The number of regions had a relatively small effect (although this effect was larger in Experiment 2). These findings indicate that the geometry of the occluding contour is a critical factor in the interpretation of accretion/deleting, and future models of 3D interpretation involving accretion/deletion must include contour geometry as a key component.

We propose a novel framework for perceptual grouping based on the idea of mixture models, called Bayesian hierarchical grouping (BHG). In BHG, we assume that the configuration of image elements is generated by a mixture of distinct objects, each of which generates image elements according to some generative assumptions. Grouping, in this framework, means estimating the number and the parameters of the mixture components that generated the image, including estimating which image elements are "owned" by which objects. We present a tractable implementation of the framework, based on the hierarchical clustering approach of Heller and Ghahramani (2005). We illustrate it with examples drawn from a number of classical perceptual grouping problems, including dot clustering, contour integration, and part decomposition. Our approach yields an intuitive hierarchical representation of image elements, giving an explicit decomposition of the image into mixture components, along with estimates of the probability of various candidate decompositions. We show that BHG accounts well for a diverse range of empirical data drawn from the literature. Because BHG provides a principled quantification of the plausibility of grouping interpretations over a wide range of grouping problems, we argue that it provides an appealing unifying account of the elusive Gestalt notion of Prägnanz.

Accretion-deletion is widely considered a decisive cue to surface depth ordering, with the accreting or deleting surface interpreted as behind an adjoining surface. However, Froyen, Feldman, and Singh (2013) have shown that when accretion-deletion occurs on both sides of a contour, accreting-deleting regions can also be perceived as in front and as self-occluding due to rotation in three dimensions. In this study we ask whether geometric figure-ground cues can override the traditional "depth from accretion-deletion" interpretation even when accretion-deletion takes place only on one side of a contour. We used two tasks: a relative-depth task (front/back), and a motion-classification task (translation/rotation). We conducted two experiments, in which texture in only one set of alternating regions was moving; the other set was static. Contrary to the traditional interpretation of accretion-deletion, the moving convex and symmetric regions were perceived as figural and rotating in three dimensions in roughly half of the trials. In the second experiment, giving different motion directions to the moving regions (thereby weakening motion-based grouping) further weakened the traditional accretion-deletion interpretation. Our results show that the standard "depth from accretion-deletion" interpretation is overridden by static geometric cues to figure-ground. Overall, the results demonstrate a rich interaction between accretion-deletion, figure-ground, and structure from motion that is not captured by existing models of depth from motion.

We present a unified Bayesian approach to shape representation and related problems in perceptual organization, including part decomposition, shape similarity, figure/ground estimation, and 3D shape. The approach is based on the idea of estimating the skeletal structure most likely to have generated the observed shape via a process of stochastic “growth.” We survey the approach briefly and show how it can be extended in a principled way to solve a wide array of related problems.

We present a novel phenomenon involving an interaction between accretion deletion, figure-ground interpretation, and structure-from-motion. Our displays contain alternating light and dark vertical regions in which random-dot textures moved horizontally at constant speed but in opposite directions in alternating regions. This motion is consistent with all the light regions in front, with the dark regions completing amodally into a single large surface moving in the background, or vice versa. Surprisingly, the regions that are perceived as figural are also perceived as 3-D volumes rotating in depth (like rotating columns)—despite the fact that dot motion is not consistent with 3-D rotation. In a series of experiments, we found we could manipulate which set of regions is perceived as rotating volumes simply by varying known geometric cues to figure ground, including convexity, parallelism, symmetry, and relative area. Subjects indicated which colored regions they perceived as rotating. For our displays we found convexity to be a stronger cue than either symmetry or parallelism. We furthermore found a smooth monotonic decay of the proportion by which subjects perceive symmetric regions as figural, as a function of their relative area. Our results reveal an intriguing new interaction between accretion-deletion, figure-ground, and 3-D motion that is not captured by existing models. They also provide an effective tool for measuring figure-ground perception.