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...

We present a purely vision-based scheme for learning a parsimonious representation of an open environment. Using simple exploration behaviours, our system constructs a graph of appropriately chosen views. To navigate between views connected in the graph, we employ a homing strategy inspired by findings of insect ethology. Simulations and robot experiments demonstrate the feasibility of the proposed approach. Introduction 1 To survive in unpredictable and sometimes hostile environments animals have developed powerful strategies to find back to their shelter or to a previously visited food source. Successful navigation can already be achieved using simple mechanisms such as association of landmarks with movements (Wehner et al. 1996) or tracking of environmental features (Collett 1996). To understand more complex forms of spatial behaviour like finding shortcuts, however, we have to go beyond reactive control strategies, towards systems with internal states. In as far as they ...

the proof of Corollary 1.1 in the actual published paper. We havechanged the bottom index of the second sum from a0toa1. As of Sept. 21, 1994 another typo has been xed. page 60, column 2, beginning of line 9 should read C T(a;a+d) instead of T (a; a + d).

A major problem a visual system faces is how to fit the large intensity variation of natural image streams into the limited dynamic range of its neurons. One of the means to accomplish this is through the use of gain control. In order to investigate this, natural time series of intensities were measured, as well as the responses of blowfly photoreceptors and Large Monopolar Cells (LMCs) to these time series. Time series representative of what each photoreceptor of a real visual system would normally receive were measured with an optical system measuring the light intensity of a spot comparable to the field of view of single human foveal cones. This system was worn on a head-band by a freely walking person. Resulting time series have rms-contrasts ranging from an average of 0.45 for 1 second segments to 1.39 for 100 second segments (both when limited to frequencies up to 100 Hz). Power spectra behave approximately as 1/f (f: temporal frequency). Measured time series were subsequently presented to fly photoreceptors and LMCs by playing them back on an LED. The results show that fast gain controls indeed keep the response within the dynamic range of the cells and that a large part of this range is actually used for packing the information in natural time series.

In visual homing tasks, animals as well as robots can compute their movements from the current view and a snapshot taken at a home position. Solving this problem exactly would require knowledge about the distances to visible landmarks, information, which is not directly available to passive vision systems. We propose a homing scheme that dispenses with accurate distance information by using parameterized disparity fields. These are obtained from an approximation that incorporates prior knowledge about perspective distortions of the visual environment. A mathematical analysis proves that the approximation does not prevent the scheme from approaching the goal with arbitrary accuracy. Mobile robot experiments are used to demonstrate the practical feasibility of the approach. 1 Introduction For many animal species it is vital to be able to find their way back to a shelter or to a rewarding food source. In particular, flying animals cannot rely on idiothetic information fo...

Information theory has recently been employed to specify more precisely than has hitherto been possible man's capacity in certain sensory, perceptual, and perceptual-motor functions

In our simulations with simple recurrent networks we demonstrate that small artificial languages are learnt differently depending on their basic word order. We show that verb-initial languages are difficult to learn, reflecting the lower frequency of verbinitial natural languages. We try to go beyond mere simulations proposing two objective mathematical measures to explain our results. 1

ABSTRACT The Wiener-Lee-Schetzen method for the identification of a nonlinear system through white gaussian noise stimulation was applied to the transient light growth response ofthe sporangiophore of Phycomyces. In order to cover a moderate dynamic range of light intensity I, the input variable was defined to be log 1. The experiments were performed in the normal range of light intensity, centered about o = 10-6 W//cm2. The kernels of the Wiener functionals were computed up to second order. Within the range of a few decades the system is reasonably linear with log 1. The main nonlinear feature of the second-order kernel corresponds to the property of rectification. Power spectral analysis reveals that the slow dynamics of the system are of at least fifth order. The system can be represented approximately by a linear transfer function, including a first-order high-pass (adaptation) filter with a 4 min time constant and an underdamped fourth-order low-pass filter. Accordingly a linear electronic circuit was constructed to simulate the small scale response characteristics. In terms of the adaptation model of Delbruck and Reichardt (1956,-in Cellular Mechanisms in Differentiation and Growth, Princeton University Press), kernels were deduced for the dynamic dependence of the growth velocity (output) on the "subjective intensity, " a presumed internal variable. Finally the linear electronic simulator above was generalized to accommodate the large scale nonlinearity of the adaptation model and to serve as a tool for deeper tests ofthe model.

Information theory has recently been employed to specify more precisely than has hitherto been possible man's capacity in certain sensory, perceptual, and perceptual-motor functions

Abstract: This paper seeks to identify what antecedents of power make it more or less likely for people to survive in a life-threatening situation. In particular, we look at the Titanic disaster as the life or death situation. Maritime disasters can be interpreted as quasi-natural experiment because every person is affected by the shock True human nature becomes apparent in such a dangerous situation. Five antecedents of power are distinguished: physical strength, economic resources, nationality, social and moral factors. This empirical analysis supports the notion that power is a key determinant in extreme situations of life or death.