Personality Organizations, Psychiatric Severity, and Self and Object Representations.

This study examined the hypothesis that psychotic, borderline, and neurotic personality organizations (POs) present a progressive differentiation between self and object representations and an increasing integration of their bad and good aspects. Fifty patients participated in the study. Measures included scales of self and object representations (S. J. Blatt, S. A. Bers, & C. E. Schaffer, 1993; S. J. Blatt, H. Wiseman, E. Prince-Gibson, & C. Gatt, 1991), as well as the Personality Organization Diagnostic Form (L. Diguer & L. Normandin, 1997) and estimations of psychiatric severity. Results showed that PO groups differed in terms of the integration of the object and its valence. It was also observed that although object and self representations were closely intertwined, the latter showed more discrimination between POs than the former. Psychiatric severity was shown to correlate more with object representations than self representations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

On Demand Solid Texture Synthesis Using Deep 3D Networks

This paper describes a novel approach for on demand volumetric texture synthesis based on a deep learning framework that allows for the generation of high-quality three-dimensional (3D) data at interactive rates. Based on a few example images of textures, a generative network is trained to synthesize coherent portions of solid textures of arbitrary sizes that reproduce the visual characteristics of the examples along some directions. To cope with memory limitations and computation complexity that are inherent to both high resolution and 3D processing on the GPU, only 2D textures referred to as ‘slices’ are generated during the training stage. These synthetic textures are compared to exemplar images via a perceptual loss function based on a pre-trained deep network. The proposed network is very light (less than 100k parameters), therefore it only requires sustainable training (i.e. few hours) and is capable of very fast generation (around a second for 256³ voxels) on a single GPU. Integrated with a spatially seeded pseudo-random number generator (PRNG) the proposed generator network directly returns a color value given a set of 3D coordinates. The synthesized volumes have good visual results that are at least equivalent to the state-of-the-art patch-based approaches. They are naturally seamlessly tileable and can be fully generated in parallel.     

Self‐similarity for accurate compression of point sampled surfaces

Most surfaces, be it from a fine‐art artifact or a mechanical object, are characterized by a strong self‐similarity. This property finds its source in the natural structures of objects but also in the fabrication processes: regularity of the sculpting technique, or machine tool. In this paper, we propose to exploit the self‐similarity of the underlying shapes for compressing point cloud surfaces which can contain millions of points at a very high precision. Our approach locally resamples the point cloud in order to highlight the self‐similarity of the shape, while remaining consistent with the original shape and the scanner precision. It then uses this self‐similarity to create an ad hoc dictionary on which the local neighborhoods will be sparsely represented, thus allowing for a light‐weight representation of the total surface. We demonstrate the validity of our approach on several point clouds from fine‐arts and mechanical objects, as well as a urban scene. In addition, we show that our approach also achieves a filtering of noise whose magnitude is smaller than the scanner precision.     

Real‐Time Modelling of Fibrous Muscle

Relatively recently it has become apparent that providing human kind with a better healthcare requires personalized, predictive and integrative medicine, for which the building of virtual physiological human (VPH) framework accessible via virtual patient avatar is necessary. Real‐time modelling and visual exploration of such a complex avatar is a challenging task. In this paper, we propose a real‐time method for automatic modelling of an arbitrarily large number of muscle fibres in the volume of a muscle represented by its surface mesh. The method is based on an iterative morphing of predefined fibres template into the muscle volume exploiting harmonic scalar field computed on the surface of muscle. Experiments with muscles of thighs and pelvis show that the method produces realistic shapes of fibres. Our sequential VTK‐based C++ implementation is capable of producing 64 fine fibres within a muscle of 10K triangles in less than 170 ms on commodity hardware making the method suitable for VPH purposes as well as for interactive educational medical software.     

Feature‐Preserving Surface Completion Using Four Points

We present a user‐guided, semi‐automatic approach to completing large holes in a mesh. The reconstruction of the missing features in such holes is usually ambiguous. Thus, unsupervised methods may produce unsatisfactory results. To overcome this problem, we let the user indicate constraints by providing merely four points per important feature curve on the mesh. Our algorithm regards this input as an indication of an important broken feature curve. Our completion is formulated as a global energy minimization problem, with user‐defined spatial‐coherence constraints, allows for completion that adheres to the existing features. We demonstrate the method on example problems that are not handled satisfactorily by fully automatic methods.     

China, 1860: A photographic album by Felice Beato

Abstract

The documentation of wars had become a significant feature of photography by the 1860s. As the camera's advantages became apparent, photographers gradually took the place of the graphic artists and painters who had previously accompanied military and diplomatic missions. The camera could reproduce reality in minute detail and an infinite number of prints were possible from each negative. Its precision as a recorder, coupled with its apparent objectivity, also made it a potentially powerful tool of propaganda.     

Crossing the divide: Infants discriminate small from large numerosities.

Although young infants have repeatedly demonstrated successful numerosity discrimination across large sets when the number of items in the sets changes twofold (E. M. Brannon, S. Abbott, & D. J. Lutz, 2004; J. N. Wood & E. S. Spelke, 2005; F. Xu & E. S. Spelke, 2000), they consistently fail to discriminate a twofold change in number when one set is large and the other is small (     

Graph-based representations and techniques for image processing and image analysis

In this paper we will discuss the use of some graph-based representations and techniques for image processing and analysis. Instead of making an extensive review of the graph techniques in this field, we will explain how we are using these techniques in an active vision system for an autonomous mobile robot developed in the Institut de Robòtica i Informàtica Industrial within the project “Active Vision System with Automatic Learning Capacity for Industrial Applications (CICYT TAP98-0473)”. Specifically we will discuss the use of graph-based representations and techniques for image segmentation, image perceptual grouping and object recognition. We first present a generalisation of a graph partitioning greedy algorithm for colour image segmentation. Next we describe a novel fusion of colour-based segmentation and depth from stereo that yields a graph representing every object in the scene. Finally we describe a new representation of a set of attributed graphs (AGs), denominated function-described graphs (FDGs), a distance measure for matching AGs with FDGs and some applications for robot vision.