Li, Y. E. and Jenkin, M. R. M. Shape from rotation using stereo. Proc. Vision Interace '92, 1992.
THis paper examines the construction of a detailed 3D surface model of an object rotating in front of a stationary video camera. An algorithm is developed which integrates repeated stereo views of a rotating object into a 3-D model of the object. Starting with disparity estimates obtained using an existing stereo algorithm, the algorithm presented here obtains the true depth of the recovered points. As the object is rotated in front of the camea, these points are then used to construct an octree representation of the object. The resulting representation provides a full 3D representation of the objects visible exterior surfaces.
Jenkin, M., Milios, E., and Tsotsos, J. TRISH: The Toronto-IRIS Stereo Head, Proc. SPIE Vol. 1708 Applications of Artificial Intelligence X: Machine Vision and Robotics, 1992.
This paper introduces and motivates the design of a controllable stereo vision head. TRISH (The Toronto IRIS STereo Head) is a binocular camera mount, consisting of two AGC, fixed focal length colour cameras forming a verging stereo pair. TRISH is capable of version (rotation of the eyes about the vertical axis so as to maintain a constant disparity), vergence (rotation of the eyes about the vertical axis so as to change the dispartiy), pan (rotaiton of the entire head about the vertical axis), and tilt (rotation of the eyes about the horizontal axis). One novel characteristic of the design is that the two cameras can rotate about their own optical axes (torsion). Torsion movement makes it possible to minimze the vertical component of the two-dimensional search which is associated with stereo processing in verging stereo systems.
Dudek, G., Jenkin, M., Milios, E., and Wilkes, D. Reflections on modelling a sonar range sensor, Technical Report, Centre for Intelligent Machines, McGill University, CIM-92-9, 1992. Abstract With the advent of inexpensive off-the-shelf sonar ranging units sonar has become a common sensor on mobile robotic platforms. Many different algorithms have been proposed to obtain environmental layout and other structural information by integrating sonar measurements from multiple positions and/or sensors. Given perfect distance measurements and telemetry, this integration can be fairly simple. Although sonar has become a ubiquitous sensor in mobile robotic systems, surprisingly few results are available data interpretation strategies are often very simple and surprisingly few results are available that accurately model the typical behaviour of the sensor under such conditions. This paper considers some of the potential causes of sonar errors, their effect on surface or object recovery, and then develops a simulation-based model of sonar range sensing for robot navigation that accounts for multiple reflections of the sonar signal between transmission and reception. This gives more realistic results than previous models. The approach is based on simulation of the reflection and diffraction of sonar rays from reflecting surfaces until they are attenuated beyond detectabililty or return to the receiver. Parameters of the model include frequency, minimum and maximum range, and signal detection threshold (relative to emitted signal strength, after lienar gain compensation). Finally, the usefulness of the model to the development of more effective algorithms for the interpretation of sonar data is discussed.
