Visual computation of egomotion using an image interpolation technique

A novel technique is presented for the computation of the parameters of egomotion of a mobile device, such as a robot or a mechanical arm, equipped with two visual sensors. Each sensor captures a panoramic view of the environment. We show that the parameters of egomotion can be computed by interpolating the position of the image captured by one of the sensors at the robot's present location, with respect to the images captured by the two sensors at the robot's previous location. The algorithm delivers the distance travelled and angle rotated, without the explicit measurement or integration of velocity fields. The result is obtained in a single step, without any iteration or successive approximation. Tests of the algorithm on real and synthetic images reveal an accuracy to within 5% of the actual motion. Implementation of the algorithm on a mobile robot reveals that stepwise rotation and translation can be measured to within 10% accuracy in a three-dimensional world of unknown structure. The position and orientation of the robot at the end of a 30-step trajectory can be estimated with accuracies of 5% and 5°, respectively.     

An active method of extracting egomotion parameters from optical flow

Instead of the former passive method characterized by a camera fixed on a translating and rotating vehicle, an active method characterized by tracking an object at the center of visual field is proposed. The method extracts egomotion parameters such as the instantaneous direction of translation, the axis of rotation and its angular velocity. A unit spherical surface is used as the projection surface.The theory allows clear vision where needed at the center of the visual field, and simultaneously permits the extraction of egomotion parameters from the periphery of the visual field.     

The representation of egomotion in the human brain

An essential function of visual processing is to establish the position of the body in space and, in concert with the other sense systems, to monitor movement of the whole body, or "egomotion." A key cue to egomotion is optic flow. For example, forward motion through the environment generates an expanding pattern of flow on the retina, and (with eyes fixed centrally) the direction of heading corresponds to the center of expansion [1]. In macaques, visual cortical area MST is sensitive to optic-flow structure [2, 3], and it has been suggested that MST has a central role in the computation of heading [4]. However, here we identify two areas of the human brain that represent visual cues to egomotion more directly than does MST. These areas respond strongly to a single optic-flow stimulus but become relatively unresponsive when the stimulus is surrounded with further flow patches and thereby made inconsistent with egomotion. One is putative area VIP in the anterior portion of the intraparietal sulcus. The other is a new visual area, which we refer to as cingulate sulcus visual area (CSv). Areas V1-V4 and MT respond about equally to both types of flow stimulus. MST has intermediate properties, responding well to multiple patches but with a modest preference for a single, egomotion-compatible patch. We suggest that MST is merely an intermediate processing stage for visual cues to egomotion and that such cues are more comprehensively encoded by VIP and CSv.     

Cardinal directions for visual optic flow.

As we move through our environment, the flow of deforming images on the retinae provides a rich source of information about the three-dimensional structure of the external world and how to navigate through it. Recent evidence from psychophysical [1] [2] [3] [4], electrophysiological [5] [6] [7] [8] [9] and imaging [10] [11] studies suggests that there are neurons in the primate visual system - in the medial superior temporal cortex - that are specialised to respond to this type of complex 'optic flow' motion. In principle, optic flow could be encoded by a small number of neural mechanisms tuned to 'cardinal directions', including radial and circular motion [12] [13]. There is little support for this idea at present, however, from either physiological [6] [7] or psychophysical [14] research. We have measured the sensitivity of human subjects for detection of motion and for discrimination of motion direction over a wide and densely sampled range of complex motions. Average sensitivity was higher for inward and outward radial movement and for both directions of rotation, consistent with the existence of detectors tuned to these four types of motion. Principle component analysis revealed two clear components, one for radial stimuli (outward and inward) and the other for circular stimuli (clockwise and counter-clock-wise). The results imply that the mechanisms that analyse optic flow in humans tend to be tuned to the cardinal axes of radial and rotational motion.     

Methods for determination of optic nerve blood flow

A variety of studies have been conducted over the past two decades to determine if decreased optic nerve blood flow has a role in the etiology of glaucomatous nerve damage. Five basic methods have been employed in examining blood flow. Invasive studies, utilizing electrodes placed in the optic nerve head, represent one of the first attempts to measure blood flow. More recently, the methodologies have included axoplasmic flow analysis, microspheres, radioactive tracers such as iodoantipyrine, and laser doppler measurements. The results of these studies are inconclusive and frequently contradictory. When the studies are grouped by methodology, only the iodoantipyrine data are consistent. While each of the experimental techniques has limitations, iodoantipyrine appears to have better resolution than either invasive studies or microspheres.     

An algol program for the computation of empiric regressions

An explanation is given about the meaning of empirical regression and on the domain of application of this biomathematical-statistical procedure. It may be helpful in data handling after the measurements and in a first stage of data processing especially if there is a large amount of datas. An empirical regression can provide the basis for a functional relationship analysis by giving hints for the choice of empirical mathematical functions. This will be useful and necessary in such cases where the measured values have a greater dispersion and one wants to get an analytical expression for the course of measured points. In the appendix a program listing of the ALGOL-program for empirical regression is presented. Detailed remarks are made in the text concerning the program structure, the data input and output resp. the program control parameters to enable the biological or medical user to adapt the program to their special problems without the help by a mathematician, and neither with deeper knowledge of mathematics nor with detailed insight to computer technical aspects of data processing.     

Nocturnal insects use optic flow for flight control

To avoid collisions when navigating through cluttered environments, flying insects must control their flight so that their sensory systems have time to detect obstacles and avoid them. To do this, day-active insects rely primarily on the pattern of apparent motion generated on the retina during flight (optic flow). However, many flying insects are active at night, when obtaining reliable visual information for flight control presents much more of a challenge. To assess whether nocturnal flying insects also rely on optic flow cues to control flight in dim light, we recorded flights of the nocturnal neotropical sweat bee, Megalopta genalis, flying along an experimental tunnel when: (i) the visual texture on each wall generated strong horizontal (front-to-back) optic flow cues, (ii) the texture on only one wall generated these cues, and (iii) horizontal optic flow cues were removed from both walls. We find that Megalopta increase their groundspeed when horizontal motion cues in the tunnel are reduced (conditions (ii) and (iii)). However, differences in the amount of horizontal optic flow on each wall of the tunnel (condition (ii)) do not affect the centred position of the bee within the flight tunnel. To better understand the behavioural response of Megalopta, we repeated the experiments on day-active bumble-bees (Bombus terrestris). Overall, our findings demonstrate that despite the limitations imposed by dim light, Megalopta-like their day-active relatives-rely heavily on vision to control flight, but that they use visual cues in a different manner from diurnal insects.     

An improved surface-based method for DNA computation

DNA computing is a novel method for solving a class of intractable computational problems, in which the computing time can grow exponentially with problem size. Up to now, many accomplishments have been achieved to improve its performance and increase its reliability, among which a surface-based method is an efficient candidate. In this paper, the surface-based approach proposed by Liu, Q., Wang, L., Frutos, A.G., Condon, A.E., Corn, R.M., and Smith, L.M., 2000, DNA computing on surfaces. Nature 403, 175-179 is analyzed and an improved surface-based method for DNA computation (i.e. the hybrid DNA/optical computing method) is proposed. Compared with Liu et al.'s approach, our method has some significant advantages such as low cost, short operating time, reusable surface and simple experimental steps. Moreover, the concept of combining easily patterned DNA computing steps with equally parallel, but generally uniform and not easily patterned optical computing steps is an important new direction.     

Multiscale optical flow computation from the monogenic signal

We have developed an algorithm for the estimation of cardiac motion from medical images. The algorithm exploits monogenic signal theory, recently introduced as an N-dimensional generalization of the analytic signal. The displacement is computed locally by assuming the conservation of the monogenic phase over time. A local affine displacement model replaces the standard translation model to account for more complex motions as contraction/expansion and shear. A coarse-to-fine B-spline scheme allows a robust and effective computation of the models parameters and a pyramidal refinement scheme helps handle large motions. Robustness against noise is increased by replacing the standard pointwise computation of the monogenic orientation with a more robust least-squares orientation estimate. This paper reviews the results obtained on simulated cardiac images from different modalities, namely 2D and 3D cardiac ultrasound and tagged magnetic resonance. We also show how the proposed algorithm represents a valuable alternative to state-of-the-art algorithms in the respective fields.