Jepson, A. D. and Jenkin, M. R. M., The fast computation of disparity from phase differences, Proc. IEEE CVPR, 398-403, 1989.
Previous work has demonstrated that the task of recovering local disparity measurements can be reduced to the task of measuring the local phase between bandpass signals extracted from the left and right cameras. In computing this local phase difference, earlier algorithms expressed the computational task as a nonlinear differential equation to be solved at each image point. Although this approach has great appeal as a model for biological disparity measurement, the solving of a differential equation at a large number of image points and disparities makes the algorithm unsuitable for serial digital computer applications. Here, the authors demonstrate how the approach of recovering disparity from the measurement of local phase differences can be accomplished without the computational expense exhibited by previous algorithms. This disparity measurement technique is embedded within a simple coarse-to-fine stereopsis similar to the algorithm proposed by H.K. Nishihara (1984) and the resulting algorithm is applied to a number of stereo pairs.
Dudek, G., Jenkin, M., Milios, E., and Wilkes, D., Using multiple markers in graph exploration, Proc. SPIE Vol 1198 Mobile Robots IV, 77-87, 1989
A fundamental problem in robotics is that of exploring an unknown environment. Most current approaches to exploratino make use of a global distance metric that is used to relate past sensory experiences to local measurements. Rather than rely on such an assumption we consdier the more general problem of exploration without a distance metric, as is typical of exploring using only visual information: we propose robot exploration as graph building. IN earlier papers we have shown that it is not possible for a robot to successfully explore a metricless environment without aid, but that by augmenting the robot with a single marker (which can be put down or picked up at will) it is possible for a robot to map its environment[1]. In this paper we present the extension of our algorithm to the case of k markers, and comment on the resulting decrease in time for exploration.By defining a minimal model for the world and the sensory ability of the robot, we separate spatial reasoning from visual perception. In this paper we deal only with the spatial reasoning component of the exploration problem, and assume that visual perception can identify the marker and the edges incident on the current location.
Jenkin, M. R. M. and Jepson, A. D., Measuring trajectory, Proc. IEEE Workshop on Visual Motion, Irvine, CA, 31-37, 1989.
In this paper we address the task of measuring the trajectory of structure in three-space without prior form recognition. We demonstrate how binocular detectors can be constracted that are tuned to particular inter-ocular velocity combinations. These "trajectory detectors" responds over a range of disparities (they are not tuned to a particular disparity), and signal the motion of structure in the environment with a particular trajectory in disparity space. The measured trajectory could be used by later processes to segment an image based upon coherence in three-dimensional motion of structure, or to quickly determine if the trajectory of an object presents a possible threat to the observer.
