Perceptual Organization, Figure-Ground, Attention and Saliency

Notions of figure-ground, inside-outside are difficult to define in a computational sense, yet seem intuitively meaningful. We propose that "figure" is an attention-directed region of visual information processing, and has a non-discrete boundary. Associated with "figure" is a coordinate frame and a "frame curve" which helps initiate the shape recognition process by selecting and grouping convex image chunks for later matching- to-model. We show that human perception is biased to see chunks outside the frame as more salient than those inside. Specific tasks, however, can reverse this bias. Near/far, top/bottom and expansion/contraction also behave similarly.

Levantamento pedológico de uma área-piloto relacionada ao Projeto BiosBrasil (Conservation and Sustainable Management of Below-Ground Biodiversity: Phase I), município de Benjamin Constant (AM): janela 6.

2005

Solos das áreas-piloto do Projeto BiosBrasil (Conservation and Sustainable Management of Below-Ground Biodiversity: Phase I), Município de Benjamin Constant, Estado do Amazonas.

2005

Levantamento pedológico de uma área-piloto relacionada ao Projeto BiosBrasil (Conservation and Sustainable Management of Below-Ground Biodiversity: Phase I), Município de Benjamin Constant (AM): Janela 6

2005

Solos das áreas-piloto do Projeto BiosBrasil (Conservation and Sustainable Management of Below-Ground Biodiversity: Phase I), Município de Benjamin Constant, Estado do Amazonas

2005

Levantamento pedológico de uma área-piloto relacionada ao projeto BiosBrasil (Conservation and Sustainable Management of Below-Ground Biodiversity: Phase I), Município de Benjamin Constant (AM): janela 6.

2005

Solos das áreas-piloto do projeto BiosBrasil (Conservation and Sustainable Management of Below-Ground Biodiversity: Phase I), município de Benjamin Constant, Estado do Amazonas.

2005

Levantamento do Uso e Cobertura da Terra de Seis Áreas Amostrais Relacionadas ao Projeto BiosBrasil (Conservation and Sustainable Management of Below-Ground Biodiversity:Phase I), Município de Benjamin Constant (AM).

2005

Ab initio configuration-interaction study of the ground and low-lying electronic states of NiI

For the first time, we have studied the potential-energy curves, spectroscopic terms, vibrational levels, and the spectroscopic constants of the ground and low-lying excited states of NiI by employing the complete active space self-consistent-field method with relativistic effective core potentials followed by multireference configuration-interaction calculations. We have identified six low-lying electronic states of NiI with doublet spin multiplicities, including three states of Delta symmetry and three states of Pi symmetry of the molecule within 15 000 cm(-1). The lowest (2)Delta state is identified as the ground state of NiI, and the lowest (2)Pi state is found at 2174.56 cm(-1) above it. These results fully support the previous conclusion of the observed spectra although our computational energy separation of the two states is obviously larger than that of the experimental values. The present calculations show that the low-lying excited states [13.9] (2)Pi and [14.6] (2)Delta are 3 (2)Pi and 3 (2)Delta electronic states of NiI, respectively. Our computed spectroscopic terms, vibrational levels, and spectroscopic constants for them are in good agreement with the experimental data available at present. In the present work we have not only suggested assignments for the observed states but also computed more electronic states that are yet to be observed experimentally. (c) 2005 American Institute of Physics.

Dedicated global optimization search for ground state silica nanoclusters: (SiO2)(N) (N=6-12)

Flikkema, E., & Bromley, S. T. (2004). Dedicated global optimization search for ground state silica nanoclusters: (SiO2)(N) (N=6-12). Journal of Physical Chemistry B, 108 (28), 9638-9645. RAE2008

Boundary, Brightness, and Depth Interactions During Preattentive Representation and Attentive Recognition of Figure and Ground

This article applies a recent theory of 3-D biological vision, called FACADE Theory, to explain several percepts which Kanizsa pioneered. These include 3-D pop-out of an occluding form in front of an occluded form, leading to completion and recognition of the occluded form; 3-D transparent and opaque percepts of Kanizsa squares, with and without Varin wedges; and interactions between percepts of illusory contours, brightness, and depth in response to 2-D Kanizsa images. These explanations clarify how a partially occluded object representation can be completed for purposes of object recognition, without the completed part of the representation necessarily being seen. The theory traces these percepts to neural mechanisms that compensate for measurement uncertainty and complementarity at individual cortical processing stages by using parallel and hierarchical interactions among several cortical processing stages. These interactions are modelled by a Boundary Contour System (BCS) that generates emergent boundary segmentations and a complementary Feature Contour System (FCS) that fills-in surface representations of brightness, color, and depth. The BCS and FCS interact reciprocally with an Object Recognition System (ORS) that binds BCS boundary and FCS surface representations into attentive object representations. The BCS models the parvocellular LGN→Interblob→Interstripe→V4 cortical processing stream, the FCS models the parvocellular LGN→Blob→Thin Stripe→V4 cortical processing stream, and the ORS models inferotemporal cortex.

Figure-Ground Separation

Air Force Office of Scientific Research (F49620-92-J-0499); Advanced Research Projects Agency (ONR N00014-92-J-4015); Office of Naval Research (N00014-91-J-4100)

A Neural Network Architecture for Figure-ground Separation of Connected Scenic Figures

A neural network model, called an FBF network, is proposed for automatic parallel separation of multiple image figures from each other and their backgrounds in noisy grayscale or multi-colored images. The figures can then be processed in parallel by an array of self-organizing Adaptive Resonance Theory (ART) neural networks for automatic target recognition. An FBF network can automatically separate the disconnected but interleaved spirals that Minsky and Papert introduced in their book Perceptrons. The network's design also clarifies why humans cannot rapidly separate interleaved spirals, yet can rapidly detect conjunctions of disparity and color, or of disparity and motion, that distinguish target figures from surrounding distractors. Figure-ground separation is accomplished by iterating operations of a Feature Contour System (FCS) and a Boundary Contour System (BCS) in the order FCS-BCS-FCS, hence the term FBF, that have been derived from an analysis of biological vision. The FCS operations include the use of nonlinear shunting networks to compensate for variable illumination and nonlinear diffusion networks to control filling-in. A key new feature of an FBF network is the use of filling-in for figure-ground separation. The BCS operations include oriented filters joined to competitive and cooperative interactions designed to detect, regularize, and complete boundaries in up to 50 percent noise, while suppressing the noise. A modified CORT-X filter is described which uses both on-cells and off-cells to generate a boundary segmentation from a noisy image.