Shape recognition and classification in electro-sensing

This paper aims at advancing the field of electro-sensing. It exhibits the physical mechanism underlying shape perception for weakly electric fish. These fish orient themselves at night in complete darkness by employing their active electrolocation system. They generate a stable, high-frequency, weak electric field and perceive the transdermal potential modulations caused by a nearby target with different admittivity than the surrounding water. In this paper, we explain how weakly electric fish might identify and classify a target, knowing by advance that the latter belongs to a certain collection of shapes. Our model of the weakly electric fish relies on differential imaging, i.e., by forming an image from the perturbations of the field due to targets, and physics-based classification. The electric fish would first locate the target using a specific location search algorithm. Then it could extract, from the perturbations of the electric field, generalized (or high-order) polarization tensors of the target. Computing, from the extracted features, invariants under rigid motions and scaling yields shape descriptors. The weakly electric fish might classify a target by comparing its invariants with those of a set of learned shapes. On the other hand, when measurements are taken at multiple frequencies, the fish might exploit the shifts and use the spectral content of the generalized polarization tensors to dramatically improve the stability with respect to measurement noise of the classification procedure in electro-sensing. Surprisingly, it turns out that the first-order polarization tensor at multiple frequencies could be enough for the purpose of classification. A procedure to eliminate the background field in the case where the permittivity of the surrounding medium can be neglected, and hence improve further the stability of the classification process, is also discussed.Comment: 10 pages, 15 figure

Demonstration of a 3D vision algorithm for space applications

This paper reports an extension of the MIAG algorithm for recognition and motion parameter determination of general 3-D polyhedral objects based on model matching techniques and using movement invariants as features of object representation. Results of tests conducted on the algorithm under conditions simulating space conditions are presented

A smart telerobotic system driven by monocular vision

A robotic system that accepts autonomously generated motion and control commands is described. The system provides images from the monocular vision of a camera mounted on a robot's end effector, eliminating the need for traditional guidance targets that must be predetermined and specifically identified. The telerobotic vision system presents different views of the targeted object relative to the camera, based on a single camera image and knowledge of the target's solid geometry

Robotic space simulation integration of vision algorithms into an orbital operations simulation

In order to successfully plan and analyze future space activities, computer-based simulations of activities in low earth orbit will be required to model and integrate vision and robotic operations with vehicle dynamics and proximity operations procedures. The orbital operations simulation (OOS) is configured and enhanced as a testbed for robotic space operations. Vision integration algorithms are being developed in three areas: preprocessing, recognition, and attitude/attitude rates. The vision program (Rice University) was modified for use in the OOS. Systems integration testing is now in progress

Finite element modeling of dielectric elastomer actuators for space applications

A special actuator device with passive sensing capability based on dielectric elastomer was studied and specialized to be used in space applications. The work illustrates the research project modeling procedure adopted to simulate the mechanical behavior of this material based on a finite element theory approach. The Mooney-Rivlin’s hyperelastic and Maxwell’s electrostatic models provide the theoretical basis to describe its electro-mechanic behavior. The validation of the procedure is performed through a numerical-experimental correlation between the response of a prototype of actuator developed by the Risø Danish research center and the 3D finite element model simulations. An investigation concerning a possible application in the space environment of dielectric elastomer actuators (DEA) is also presented

Mathematics of biomimetics for active echo- and electro-sensing

Active sensing animals may inspire the development of new technologies that mimic their sensing behavior. Electric fish, for instance, orient themselves at night in complete darkness by using their active electro-sensing system. They generate a stable, relatively high-frequency, weak electric field and perceive the transdermal potential modulations caused by nearby targets with different electromagnetic properties than the surrounding water. Since they have an electric sense that allows underwater navigation, target classification and intraspecific communication, they are privileged animals for bio-inspiring man-built autonomous systems. Bats, on the other hand, process the reflected echoes due to the presence of acoustic inclusions for echolocation. In general, they use acoustic waves for most of the perceptual tasks, that range from hunting to navigating. This thesis introduces premier algorithms in electro-sensing and echo-sensing. The weakly electric fish is able to retrieve much more information about the target by approaching it. To mimic this behavior, an innovative (real-time) multi-scale method for target classification in electro-sensing is presented. The method is based on a family of transform-invariant shape descriptors computed from generalized polarization tensors (GPTs) reconstructed at multiple scales. The evidence provided by the different descriptors at each scale is fused using Dempster-Shafer Theory. Numerical simulations show that the recognition algorithm we proposed performs undoubtedly well and yields a robust classification. For real-world applications, inhomogeneous targets have to be identified. The shape descriptor-based classification algorithm is extended in order to consider inhomogenous material parameters. The approach is based on new invariants for the contracted generalized polarization tensors associated with inhomogeneous objects. The numerical simulations show that by comparing these invariants with those in a dictionary of precomputed homogeneous and inhomogeneous targets, one can successfully classify the inhomogeneous target. Another problem concerns intraspecific electro-communication for weakly electric fish. In particular, a description on how the fish circumvent the jamming issue for both electro-communication and active electro-sensing is presented. The main result is a real-time tracking algorithm, which provides a new approach to the communication problem. It finds a natural application in robotics, where efficient communication strategies are needed to be implemented by bio-inspired underwater robots. The concept of time-dependent polarization tensors (TDPTs) for the wave equation associated to a diametrically small acoustic inclusion, with constitutive parameters different from those of the background and size smaller than the operating wavelength, is used to mimic the echo-sensing capabilities of a static bat. Firstly, the solution to the Helmholtz equation is considered, and a rigorous systematic derivation of a complete asymptotic expansion of the scattered field due to the presence of the inclusion is presented. Then, by applying the Fourier transform, the corresponding time-domain expansion is readily obtained after truncating the high frequencies. The new concept of TDPTs is shown to be promising for performing imaging. Numerical simulations are presented, showing that the TDPTs reconstructed from noisy measurements allow to image fine shape details of the inclusion

Human Face Recognition

Face recognition, as the main biometric used by human beings, has become more popular for the last twenty years. Automatic recognition of human faces has many commercial and security applications in identity validation and recognition and has become one of the hottest topics in the area of image processing and pattern recognition since 1990. Availability of feasible technologies as well as the increasing request for reliable security systems in today’s world has been a motivation for many researchers to develop new methods for face recognition. In automatic face recognition we desire to either identify or verify one or more persons in still or video images of a scene by means of a stored database of faces. One of the important features of face recognition is its non-intrusive and non-contact property that distinguishes it from other biometrics like iris or finger print recognition that require subjects’ participation. During the last two decades several face recognition algorithms and systems have been proposed and some major advances have been achieved. As a result, the performance of face recognition systems under controlled conditions has now reached a satisfactory level. These systems, however, face some challenges in environments with variations in illumination, pose, expression, etc. The objective of this research is designing a reliable automated face recognition system which is robust under varying conditions of noise level, illumination and occlusion. A new method for illumination invariant feature extraction based on the illumination-reflectance model is proposed which is computationally efficient and does not require any prior information about the face model or illumination. A weighted voting scheme is also proposed to enhance the performance under illumination variations and also cancel occlusions. The proposed method uses mutual information and entropy of the images to generate different weights for a group of ensemble classifiers based on the input image quality. The method yields outstanding results by reducing the effect of both illumination and occlusion variations in the input face images

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 292)

This bibliography lists 192 reports, articles and other documents introduced into the NASA scientific and technical information system in December, 1986