Qualitative egomotion

3D Motion and Shape Representations in Visual Servo Control

The study of visual navigation problems requires the integration of visual processes with motor control. Most essential in approaching this integration is the study of appropriate spatiotemporal represen tations that the system computes from the imagery and that serve as interfaces to all motor activities. Since representations resulting from exact metric reconstruction of the environment have turned out to be very hard to obtain in real time, the authors argue for the necessity of representations that can be computed easily, reliably, and in real time and that recover only the information about the 3D world that is really needed to solve the navigational problems at hand. In this paper, the authors introduce a number of such rep resentations capturing aspects of 3D motion and scene structure that are used to solve navigational problems implemented in visual servo systems.

Active gaze control improves optic flow-based segmentation and steering

An observer traversing an environment actively relocates gaze to fixate objects. Evidence suggests that gaze is frequently directed toward the center of an object considered as target but more likely toward the edges of an object that appears as an obstacle. We suggest that this difference in gaze might be motivated by specific patterns of optic flow that are generated by either fixating the center or edge of an object. To support our suggestion we derive an analytical model that shows: Tangentially fixating the outer surface of an obstacle leads to strong flow discontinuities that can be used for flow-based segmentation. Fixation of the target center while gaze and heading are locked without head-, body-, or eye-rotations gives rise to a symmetric expansion flow with its center at the point being approached, which facilitates steering toward a target. We conclude that gaze control incorporates ecological constraints to improve the robustness of steering and collision avoidance by actively generating flows appropriate to solve the task.

Estimating relative camera motion from the antipodal-epipolar constraint

This paper introduces a novel antipodal-epipolar constraint on relative camera motion. By using antipodal points, which are available in large Field-of-View cameras, the translational and rotational motions of a camera are geometrically decoupled, allowing them to be separately estimated as two problems in smaller dimensions. We present a new formulation based on discrete camera motions, which works over a larger range of motions compared to previous differential techniques using antipodal points. The use of our constraints is demonstrated with two robust and practical algorithms, one based on RANSAC and the other based on Hough-like voting. As an application of the motion decoupling property, we also present a new structure-from-motion algorithm that does not require explicitly estimating rotation (it uses only the translation found with our methods). Finally, experiments involving simulations and real image sequences will demonstrate that our algorithms perform accurately and robustly, with some advantages over the state-of-the-art.

Families of stationary patterns producing illusory movement: insights into the visual system

A computational explanation of the illusory movement experienced upon extended viewing of Enigma, a static figure painted by Leviant, is presented. The explanation relies on a model for the interpretation of three-dimensional motion information contained in retinal motion measurements. This model shows that the Enigma figure is a special case of a larger class of figures exhibiting the same illusory movement and these figures are introduced here. Our explanation suggests that eye movements and/or accommodation changes cause weak retinal motion signals, which are interpreted by higher-level processes in a way that gives rise to these illusions, and proposes a number of new experiments to unravel the functional structure of the motion pathway.

Direct perception of three-dimensional motion from patterns of visual motion

Measurements of retinal motion along a set of predetermined orientations on the retina of a moving system give rise to global patterns. Because the form and location of these patterns depend purely on three-dimensional (3D) motion, the effects of 3D motion and scene structure on image motion can be globally separated. The patterns are founded on easily derivable image measurements that depend only on the sign of image motion and do not require information about optical flow. The computational theory presented here explains how the self-motion of a system can be estimated by locating these patterns.