Depth,contrast and view-based homing in outdoor scenes

Panoramic image differences can be used for view-based homing under natural outdoor conditions, because they increase smoothly with distance from a reference location (Zeil et al., J Opt Soc Am A 20(3):450–469, 2003). The particular shape, slope and depth of such image difference functions (IDFs) recorded at any one place, however, depend on a number of factors that so far have only been qualitatively identified. Here we show how the shape of difference functions depends on the depth structure and the contrast of natural scenes, by quantifying the depth- distribution of different outdoor scenes and by comparing it to the difference functions calculated with differently processed panoramic images, which were recorded at the same locations. We find (1) that IDFs and catchment areas become systematically wider as the average distance of objects increases, (2) that simple image processing operations—like subtracting the local mean, difference-of-Gaussian filtering and local contrast normalization—make difference functions robust against changes in illumination and the spurious effects of shadows, and (3) by comparing depth-dependent translational and depth-independent rotational difference functions, we show that IDFs of contrast-normalized snapshots are predominantly determined by the depth-structure and possibly also by occluding contours in a scene. We propose a model for the shape of IDFs as a tool for quantitative comparisons between the shapes of these functions in different scenes.     

The application of co-ordination dynamics to the analysis of discrete movements using table-tennis as a paradigm skill

 The purpose of this experiment was to explore the application of co-ordination dynamics to the analysis of discrete rather than cyclical movements. Subjects, standing in a fixed position, were required to return table-tennis balls delivered to different spatial locations in the direction of a fixed target. This was achieved in condition 1 by systematically scaling, from left to right and vice versa, the `spatial location' of the ball–identified as a control parameter. In condition 2, the control condition, the spatial location was varied randomly over the same range. The changes between regimes of the stroke co-ordination pattern, defined at two different levels, (1) organisational – forehand or backhand drive, and (2) kinematic–the distance of the bat at ball–bat contact relative to the leading edge of the table, were identified as collective variables, the values of which changed spontaneously at the transition points exposed by the control parameter. The switch between regimes was shown to be dependent upon the direction of scaling, i.e. a hysteresis effect was identified in both conditions. These findings confirm that the conceptual and methodological frameworks of co-ordination dynamics can be applied, appropriately, to the analysis of discrete movements. Moreover, it would seem that control parameter values (spatial location of the ball) do not necessarily have to be scaled in a systematic way in order to produce the required effects. Received: 22 April 1999 / Accepted in revised form: 8 May 2000     

A multi-step directional generalized gradient vector flow snake for target tumor segmentation in US-guided high-intensity focused ultrasound ablation

Getting precise locations of target tumors can help to ensure ablation of cancerous tissues and avoid unwanted destruction of healthy tissues in high-intensity focused ultrasound (HIFU) treatment system. Because of speckle noise and spurious boundaries in ultrasound images, traditional image segmentation methods are not suitable for achieving the precise locations of target tumors in HIFU ablation. In this paper, a multi-step directional generalized gradient vector flow snake model is introduced for target tumor segmentation. In the first step, the traditional generalized gradient vector flow (GGVF) snake is used to obtain an approximate contour of the tumor. According to the approximate contour, a new distance map is generated. Subsequently, a new directional edge map is created by calculating a scalar product of the gradients of the distance map and the initial image. In this process, the gradient directional information and the magnitude information of the distance map are used to attenuate unwanted edges and highlight the real edges in the new directional edge map. Finally, a refined GGVF field is derived from a diffusion operation of the gradient vectors of the directional edge map. The GGVF field is used to refine the tumor's contour, by directing the approximate contour to edges with the desired gradient directionality. Based on the newly developed snake model, the influences of the spurious boundaries and the speckle noise are significantly reduced in the ultrasound image segmentation. Experimental results indicate that this technique is greatly useful for target tumor segmentation in HIFU treatment system     

Simulated visual homing in desert ant natural environments: efficiency of skyline cues

Desert ants, foraging in cluttered semiarid environments, are thought to be visually guided along individual, habitual routes. While other navigational mechanisms (e.g. path integration) are well studied, the question of how ants extract reliable visual features from a complex visual scene is still largely open. This paper explores the assumption that the upper outline of ground objects formed against the sky, i.e. the skyline, provides sufficient information for visual navigation. We constructed a virtual model of the ant’s environment. In the virtual environment, panoramic images were recorded and adapted to the resolution of the desert ant’s complex eye. From these images either a skyline code or a pixel-based intensity code were extracted. Further, two homing algorithms were implemented, a modified version of the average landmark vector (ALV) model (Lambrinos et al. Robot Auton Syst 30:39–64, 2000) and a gradient ascent method. Results show less spatial aliasing for skyline coding and best homing performance for ALV homing based on skyline codes. This supports the assumption of skyline coding in visual homing of desert ants and allows novel approaches to technical outdoor navigation.     

Natal dispersal of introduced Siberian chipmunks, <Emphasis Type="Italic">Tamias sibiricus</Emphasis>, in a suburban forest

The Siberian chipmunk, Tamias sibiricus, was introduced into the suburban forest of Sénart in the late 1970s where it naturalised. Juvenile dispersal of this solitary ground-dwelling squirrel is not known, while it is an important component of the invasion process. From 2003 to 2007, mark–recapture techniques were used to determine how dispersal movements differed between year, cohort, sex and body mass. Distances moved were calculated between the location of first capture during the year of birth and the arithmetic centre of the trapping locations obtained the next year. Excluding heaviest individuals, e.g. 80 g, that must have already dispersed and thus lowered the estimation of averaged distance moved, our results shows that the dispersal distance in juvenile males (168 ± 24 m, n = 39) was greater than in females (83 ± 11 m, n = 66), with no effect detected for either year or cohort. Juveniles are thus involved in the spread of this ground squirrel, bearing in mind that movements estimated may have been underestimated due to the use of capture–mark–recapture methods on a limited trapping area.     

Estimating material parameters of human skin in vivo

An accurate mathematical representation of the mechanical behaviour of human skin is essential when simulating deformations occurring in the skin during body movements or clinical procedures. In this study constitutive stress–strain relationships based on experimental data from human skin in vivo were obtained. A series of multiaxial loading experiments were performed on the forearms of four age- and gender matched subjects. The tissue geometry, together with recorded displacements and boundary forces, were combined in an analysis using finite element modelling. A non-linear optimization technique was developed to estimate values for the material parameters of a previously published constitutive law, describing the stress–strain relationship as a non-linear anisotropic membrane. Ten sets of material parameters where estimated from the experiments, showing considerable differences in mechanical behaviour both between individual subjects as well as mirrored body locations on a single subject. The accuracy of applications that simulate large deformations of human skin could be improved by using the parameters found from the in vivo experiments as described in this study.     

Scene content selected by active vision

The primate visual system actively selects visual information from the environment for detailed processing through mechanisms of visual attention and saccadic eye movements. This study examines the statistical properties of the scene content selected by active vision. Eye movements were recorded while participants free-viewed digitized images of natural and artificial scenes. Fixation locations were determined for each image and image patches were extracted around the observed fixation locations. Measures of local contrast, local spatial correlation and spatial frequency content were calculated on the extracted image patches. Replicating previous results, local contrast was found to be greater at the points of fixation when compared to either the contrast for image patches extracted at random locations or at the observed fixation locations using an image-shuffled database. Contrary to some results and in agreement with other results in the literature, a significant decorrelation of image intensity is observed between the locations of fixation and other neighboring locations. A discussion and analysis of methodological techniques is given that provides an explanation for the discrepancy in results. The results of our analyses indicate that both the local contrast and correlation at the points of fixation are a function of image type and, furthermore, that the magnitude of these effects depend on the levels of contrast and correlation present overall in the images. Finally, the largest effect sizes in local contrast and correlation are found at distances of approximately 1 deg of visual angle, which agrees well with measures of optimal spatial scale selectivity in the visual periphery where visual information for potential saccade targets is processed.     

An image-interpolation technique for the computation of optic flow and egomotion

 A technique for measuring the motion of a rigid, textured plane in the frontoparallel plane is developed and tested on synthetic and real image sequences. The parameters of motion – translation in two dimensions, and rotation about a previously unspecified axis perpendicular to the plane – are computed by a single-stage, non-iterative process which interpolates the position of the moving image with respect to a set of reference images. The method can be extended to measure additional parameters of motion, such as expansion or shear. Advantages of the technique are that it does not require tracking of features, measurement of local image velocities or computation of high-order spatial or temporal derivatives of the image. The technique is robust to noise, and it offers a simple, novel way of tackling the ‘aperture’ problem. An application to the computation of robot egomotion is also described. Received: 3 September 1993/Accepted in revised form: 16 April 1994     

Young’s modulus of elasticity of Schlemm’s canal endothelial cells

Schlemm’s canal (SC) endothelial cells are likely important in the physiology and pathophysiology of the aqueous drainage system of the eye, particularly in glaucoma. The mechanical stiffness of these cells determines, in part, the extent to which they can support a pressure gradient and thus can be used to place limits on the flow resistance that this layer can generate in the eye. However, little is known about the biomechanical properties of SC endothelial cells. Our goal in this study was to estimate the effective Young’s modulus of elasticity of normal SC cells. To do so, we combined magnetic pulling cytometry of isolated cultured human SC cells with finite element modeling of the mechanical response of the cell to traction forces applied by adherent beads. Preliminary work showed that the immersion angles of beads attached to the SC cells had a major influence on bead response; therefore, we also measured bead immersion angle by confocal microscopy, using an empirical technique to correct for axial distortion of the confocal images. Our results showed that the upper bound for the effective Young’s modulus of elasticity of the cultured SC cells examined in this study, in central, non-nuclear regions, ranged between 1,007 and 3,053 Pa, which is similar to, although somewhat larger than values that have been measured for other endothelial cell types. We compared these values to estimates of the modulus of primate SC cells in vivo, based on images of these cells under pressure loading, and found good agreement at low intraocular pressure (8–15 mm Hg). However, increasing intraocular pressure (22–30 mm Hg) appeared to cause a significant increase in the modulus of these cells. These moduli can be used to estimate the extent to which SC cells deform in response to the pressure drop across the inner wall endothelium and thereby estimate the extent to which they can generate outflow resistance.     

Identification of Event-Related Potentials Elicited by Conceptual Mismatch Between Expectations and Self-chosen TV Images

When a voluntary action is followed by an unexpected stimulus, a late positive potential (LPP) with a posterior scalp distribution is elicited in a latency range of 500–700 ms. In the present study, we examined what type of mismatch between expectations and action outcomes was reflected by the LPP. Twelve student volunteers participated in a task simulating choice of TV programs. After choosing one of three options displayed as a cue stimulus, they viewed a second stimulus (still TV image). To manipulate the type of expectation, three kinds of cue conditions were used: thumbnail image condition (three small TV images), category label condition (three words), and no cue condition (three question marks). Over trials, the second stimulus either matched (p = .80) or mismatched (p = .20) the chosen option. As compared to matched TV images, mismatched TV images elicited a larger LPP (500–700 ms) in the thumbnail image and category label conditions. In addition, a larger centroparietal P3 (400–450 ms) was elicited to mismatched TV images in the thumbnail image condition alone. LPP reflects a conceptual mismatch between a category-based expectation and an ensuing action outcome, whereas P3 reflects a perceptual mismatch between an image-based expectation and an action outcome.     

Modelling place memory in crickets

Insects can remember and return to a place of interest using the surrounding visual cues. In previous experiments, we showed that crickets could home to an invisible cool spot in a hot environment. They did so most effectively with a natural scene surround, though they were also able to home with distinct landmarks or blank walls. Homing was not successful, however, when visual cues were removed through a dark control. Here, we compare six different models of visual homing using the same visual environments. Only models deemed biologically plausible for use by insects were implemented. The average landmark vector model and first order differential optic flow are unable to home better than chance in at least one of the visual environments. Second order differential optic flow and GradDescent on image differences can home better than chance in all visual environments, and best in the natural scene environment, but do not quantitatively match the distributions of the cricket data. Two models—centre of mass average landmark vector and RunDown on image differences—could produce the same pattern of results as observed for crickets. Both the models performed best using simple binary images and were robust to changes in resolution and image smoothing.     

Canopy-cover thematic-map generation for Military Map products using remote sensing data in inaccessible areas

Canopy cover is one of the most important elements in concealing military structures and enemy reconnaissance. In this study, we propose an algorithm for automatic generation of density measure of percent canopy cover, which is an attribute of the digital Military Map product, using high-resolution satellite images of inaccessible areas. The thematic mapping process of canopy cover can be divided into image classification, segmentation, and texture analysis. QuickBird and SPOT-5 high-resolution images are classified using Landsat images and military maps. Then, forested areas are extracted from the classified images, and closing and opening operations are executed through morphology filtering. The extracted region is divided into unit-zone objects using a segmentation technique, and the percentage of canopy cover of each object is categorized as one of four levels (0–25, 26–50, 51–75, 76–100%). Two methods were used to establish the percentage of canopy cover for each segment: the discriminant method, using statistical analysis, and the classified canopy ratio method, which calculates the percentage of forest in the segment. The discriminant method showed 48% (QuickBird) and 61% (SPOT-5) accuracy and classified canopy ratio method showed 71% (QuickBird) and 87% (SPOT-5) accuracy.     

Where did I take that snapshot? Scene-based homing by image matching

In homing tasks, the goal is often not marked by visible objects but must be inferred from the spatial relation to the visual cues in the surrounding scene. The exact computation of the goal direction would require knowledge about the distances to visible landmarks, information, which is not directly available to passive vision systems. However, if prior assumptions about typical distance distributions are used, a snapshot taken at the goal suffices to compute the goal direction from the current view. We show that most existing approaches to scene-based homing implicitly assume an isotropic landmark distribution. As an alternative, we propose a homing scheme that uses parameterized displacement fields. These are obtained from an approximation that incorporates prior knowledge about perspective distortions of the visual environment. A mathematical analysis proves that both approximations do not prevent the schemes from approaching the goal with arbitrary accuracy, but lead to different errors in the computed goal direction. Mobile robot experiments are used to test the theoretical predictions and to demonstrate the practical feasibility of the new approach. Received: 11 December 1997 / Accepted in revised form: 12 June 1998     

Predicting the eye fixation locations in the gray scale images in the visual scenes with different semantic contents

In recent years, there has been considerable interest in visual attention models (saliency map of visual attention). These models can be used to predict eye fixation locations, and thus will have many applications in various fields which leads to obtain better performance in machine vision systems. Most of these models need to be improved because they are based on bottom-up computation that does not consider top-down image semantic contents and often does not match actual eye fixation locations. In this study, we recorded the eye movements (i.e., fixations) of fourteen individuals who viewed images which consist natural (e.g., landscape, animal) and man-made (e.g., building, vehicles) scenes. We extracted the fixation locations of eye movements in two image categories. After extraction of the fixation areas (a patch around each fixation location), characteristics of these areas were evaluated as compared to non-fixation areas. The extracted features in each patch included the orientation and spatial frequency. After feature extraction phase, different statistical classifiers were trained for prediction of eye fixation locations by these features. This study connects eye-tracking results to automatic prediction of saliency regions of the images. The results showed that it is possible to predict the eye fixation locations by using of the image patches around subjects’ fixation points.     

Non-visual environmental imaging and object detection through active electrolocation in weakly electric fish

Weakly electric fish orient at night by employing active electrolocation. South American and African species emit electric signals and perceive the consequences of these emissions with epidermal electroreceptors. Objects are detected by analyzing the electric images which they project onto the animal’s electroreceptive skin surface. Electric images depend on size, distance, shape, and material of objects and on the morphology of the electric organ and the fish’s body. It is proposed that the mormyrid Gnathonemus petersii possesses two electroreceptive “foveae” at its Schnauzenorgan and its nasal region, both of which resemble the visual fovea in the retina of many animals in design, function, and behavioral use. Behavioral experiments have shown that G. petersii can determine the resistive and capacitive components of an object’s complex impedance in order to identify prey items during foraging. In addition, fish can measure the distance and three-dimensional shape of objects. In order to determine object properties during active electrolocation, the fish have to determine at least four parameters of the local signal within an object’s electric image: peak amplitude, maximal slope, image width, and waveform distortions. A crucial parameter is the object distance, which is essential for unambiguous evaluation of object properties.     

Limited contemporary gene flow and high self‐replenishment drives peripheral isolation in an endemic coral reef fish

Extensive ongoing degradation of coral reef habitats worldwide has lead to declines in abundance of coral reef fishes and local extinction of some species. Those most vulnerable are ecological specialists and endemic species. Determining connectivity between locations is vital to understanding recovery and long‐term persistence of these species following local extinction. This study explored population connectivity in the ecologically‐specialized endemic three‐striped butterflyfish (Chaetodon tricinctus) using mt and msatDNA (nuclear microsatellites) to distinguish evolutionary versus contemporary gene flow, estimate self‐replenishment and measure genetic diversity among locations at the remote Australian offshore coral reefs of Middleton Reef (MR), Elizabeth Reef (ER), Lord Howe Island (LHI), and Norfolk Island (NI). Mt and msatDNA suggested genetic differentiation of the most peripheral location (NI) from the remaining three locations (MR, ER, LHI). Despite high levels of mtDNA gene flow, there is limited msatDNA gene flow with evidence of high levels of self‐replenishment (≥76%) at all four locations. Taken together, this suggests prolonged population recovery times following population declines. The peripheral population (NI) is most vulnerable to local extinction due to its relative isolation, extreme levels of self‐replenishment (95%), and low contemporary abundance.     

Modeling boundary vector cell firing given optic flow as a cue

Boundary vector cells in entorhinal cortex fire when a rat is in locations at a specific distance from walls of an environment. This firing may originate from memory of the barrier location combined with path integration, or the firing may depend upon the apparent visual input image stream. The modeling work presented here investigates the role of optic flow, the apparent change of patterns of light on the retina, as input for boundary vector cell firing. Analytical spherical flow is used by a template model to segment walls from the ground, to estimate self-motion and the distance and allocentric direction of walls, and to detect drop-offs. Distance estimates of walls in an empty circular or rectangular box have a mean error of less than or equal to two centimeters. Integrating these estimates into a visually driven boundary vector cell model leads to the firing patterns characteristic for boundary vector cells. This suggests that optic flow can influence the firing of boundary vector cells.     

Comparison of heat dissipation response between Malaysian and Japanese males during exercise in humid heat stress

This study investigated the differences in heat dissipation response to intense heat stress during exercise in hot and humid environments between tropical and temperate indigenes with matched physical characteristics. Ten Japanese (JP) and ten Malaysian (MY) males participated in this study. Subjects performed exercise for 60 min at 55% peak oxygen uptake in 32°C air with 70% relative humidity, followed by 30 min recovery. The increase in rectal temperature (T _re) was smaller in MY during exercise compared to JP. The local sweat rate and total body mass loss were similar in both groups. Both skin blood flow and mean skin temperature was lower in MY compared to JP. A significantly greater increase in hand skin temperature was observed in MY during exercise, which is attributable to heat loss due to the greater surface area to mass ratio and large number of arteriovenous anastomoses. Also, the smaller increase in T _re in MY may be explained by the presence of a significantly greater core–skin temperature gradient in MY than JP. The thermal gradient is also a major factor in increasing the convective heat transfer from core to skin as well as skin blood flow. It is concluded that the greater core–skin temperature gradient observed in MY is responsible for the smaller increase in T _re.     

Forward shift from reverse replay

In a recent experimental paper Lee et al. (Neuron 51:639–650, 2006) showed that the firing patterns of CA1 complex-spike neurons gradually shifted forward across trials toward prospective goal locations within a recording session over multiple trials. Here we propose a simple model of this result based on the phenomenon of awake sequence reverse replay (Foster and Wilson, Nature 440(7084):615–617, 2006) which occurs when the animal pauses at the reward location. The model is based on the CA3-CA1 anatomy with modulation of CA3-CA1 synaptic plasticity by feedback from CA3 projecting CA1 interneurons. Sequence replays, which are generated in CA3 by removal of subcortical inhibition on CA1 interneurons, are recoded into the synaptic weights of individual CA1 cells. This produces spatially extended CA1 firing fields, whose response provides a value function on experienced paths toward goal locations. Simulations show that the CA1 firing fields show positive movement in center of mass toward reward locations over many trials with negative shift in first few trials, and development of positive skew.     

Automated Protein Subcellular Localization Based on Local Invariant Features

To understand the function of the encoded proteins, we need to be able to know the subcellular location of a protein. The most common method used for determining subcellular location is fluorescence microscopy which allows subcellular localizations to be imaged in high throughput. Image feature calculation has proven invaluable in the automated analysis of cellular images. This article proposes a novel method named LDPs for feature extraction based on invariant of translation and rotation from given images, the nature which is to count the local difference features of images, and the difference features are given by calculating the D-value between the gray value of the central pixel c and the gray values of eight pixels in the neighborhood. The novel method is tested on two image sets, the first set is which fluorescently tagged protein was endogenously expressed in 10 sebcellular locations, and the second set is which protein was transfected in 11 locations. A SVM was trained and tested for each image set and classification accuracies of 96.7 and 92.3 % were obtained on the endogenous and transfected sets respectively.