The mammalian visual system is endowed with a nearly infinite capacity for the recognition of patterns and objects. To have acquired this capability the visual system must have solved what is a fundamentally combinatorial prob­ lem. Any given image consists of a collection of features, consisting of local contrast borders of luminance and wavelength, distributed across the visual field. For one to detect and recognize an object within a scene, the features comprising the object must be identified and segregated from those comprising other objects. This problem is inherently difficult to solve because of the combinatorial nature of visual images. To appreciate this point, consider a simple local feature such as a small vertically oriented line segment placed within a fixed location of the visual field. When combined with other line segments, this feature can form a nearly infinite number of geometrical objects. Any one of these objects may coexist with an equally large number of other

Visual feature integration and the temporal correlation hypothesis

The goal of this paper is to present a critical survey of existing literature on human and machine recognition of faces. Machine recognition of faces has several applications, ranging from static matching of controlled photographs as in mug shots matching and credit card verification to surveillance video images. Such applications have different constraints in terms of complexity of processing requirements and thus present a wide range of different technical challenges. Over the last 20 years researchers in psychophysics, neural sciences and engineering, image processing analysis and computer vision have investigated a number of issues related to face recognition by humans and machines. Ongoing research activities have been given a renewed emphasis over the last five years. Existing techniques and systems have been tested on different sets of images of varying complexities. But very little synergism exists between studies in psychophysics and the engineering literature. Most importantly, there exists no evaluation or benchmarking studies using large databases with the image quality that arises in commercial and law enforcement applications In this paper, we first present different applications of face recognition in commercial and law enforcement sectors. This is followed by a brief overview of the literature on face recognition in the psychophysics community. We then present a detailed overview of move than 20 years of research done in the engineering community. Techniques for segmentation/location of the face, feature extraction and recognition are reviewed. Global transform and feature based methods using statistical, structural and neural classifiers are summarized. >

Human and machine recognition of faces: a survey

http://static.sif.it/SIF/resources/public/files/va2012/likos_0710.pdf

Effective interactions in soft condensed matter physics

How are the functions performed by one part of the nervous system integrated with those of another? This fundamental issue pervades virtually every aspect of brain function from sensory and cognitive processing to motor control. Yet from a physiological perspective we know very little about the neural mechanisms underlying the integration of distributed processes in the nervous system. Even the simplest of sensori-motor acts engages vast numbers of cells in many different parts of the brain. Such actions require coordination between a host of neural systems, each of which must carry out parallel computations involving large populations of interconnected neurons. It seems reasonable to assume that a mechanism or class of mechanisms has evolved to temporally coordinate the activity within and between subsystems of the central nervous system. For several reasons, neuronal rhythms have long been thought to play an important role in such coordination. Since the discovery of the Electroencephalogram (EEG) over 60 years ago it has been known that a number of structures in the mammalian brain engage in rhythmic activities. These patterned neuronal oscillations take many forms. They occur over a broad range of frequencies, and are present in a multitude of different systems in the b~ain, during a variety of different behavioral states. They are often the most salient aspect of observable electrical activity in the brain and typically encompass widespread regions of cerebral tissue. With the advent of new techniques of multielectrode recording and neural imaging, it is now within the realm of possibility 'to record from 100 single neurons simultaneously (Wilson and McNaughton, 1993), to optically measure the activity in a cortical area (Blasdel and Salama, 1986; T'so et al., 1990), or to noninvasively image the pattern of electric current flow in an alert human being performing a task (Pantev et al., 1991). These new techniques have revealed that spatially and temporally organized activity among distributed populations of cells often takes the form of synchronous rhythms. When combined with cellular neurophysiological and anatomical studies these findings provide new insights into the behavior and mechanisms controUing the coordination of activity in neuronal populations.

Synchronous oscillations in neuronal systems: mechanisms and functions.

Invertible cellular automata: a review

In this paper, we introduce two notions of being “balanced” and being “hard.” And we prove that these notions are necessary and sufficient conditions for global maps C ; → C and C → C of tessellation automata to be one to one, respectively, where CC denotes the set of all the (finite) configurations of tessellation automata.

Condition for Injectivity of global maps for tessellation automata

The self- and mutual-avoiding effects of two star polymers in a good solvent are studied by means of a simple Monte Carlo sampling technique on a cubic lattice, using an enrichment algorithm. The total number of configurations is determined as a function of the distance between the two star polymers. The radius of gyration of a single star polymer, the second virial coefficient, the effective interstar potential, and the penetration function are evaluated for 3- to 6-arm star polymers. Considerable deviation from the result of the previous naive first-order e-expansion is observed in the penetration function. We also discuss the value of the penetration function in the infinite-arm limit, according to the cone picture.

Monte Carlo study of the second virial coefficient of star polymers in a good solvent

The goal of this research is to study whether robot programs which are generated by means of genetic programming (GP) are robust. The simulated robot task is a box moving problem. In order to test the robustness of generated programs, we conduct two experiments. In the first experiment, the initial conditions of the robot are fluxed. This is to prevent the overgeneralization of the specific situations. In the second one, the robot's sensors and actuators are assumed to be noisy. As a result of experiments, we have observed that the robot behaves robustly on the both experiments. GP has generated programs which evaluate almost effective commands for each sensor state. We suppose that the robot behaves robustly due to the redundancy of the programs, and we discuss how this redundancy is realized in GP framework for our robot programs.

Robustness of robot programs generated by genetic programming

Injectivity and surjectivity of parallel maps for cellular automata

Star chains composed of arms with uniform length were generated on a simple cubic lattice by the Monte Carlo method using the enrichment algorithm, which enabled us to obtain chains with total segment numbers (N) up to 1200. The number of arms (f) ranged from 2 to 24. The radius of gyration (〈S2〉1/2), the dimensionless intrinsic viscosity (E), and the hydrodynamic radius (RH) were evaluated as functions of f and N by averaging over more than 4000 samples. The calculations of E and RH were made according to Zimm's method. It was found that the radius expansion factor (αS) for star chains with long arms obeys the relation αS2 = 1.53z2/5, which is known for long flexible linear chains, where z is the excluded volume parameter. The ratios of 〈S2〉, E, and RH of star chains to those for linear chains were evaluated as functions of f. These ratios obtained and the Flory factors for the intrinsic viscosity and RH extrapolated to N-1/2 → 0 reproduced experimental data well.

Masayuki Kimura

Papers

Condition for Injectivity of global maps for tessellation automata

Monte Carlo study of the second virial coefficient of star polymers in a good solvent

Robustness of robot programs generated by genetic programming

Injectivity and surjectivity of parallel maps for cellular automata

Dimensional and Hydrodynamic Factors for Flexible Star Polymers in the Good Solvent Limit