Issue No. 06 - June (1985 vol. 7)
Michael J. Magee , Laboratory for Image and Signal Analysis, the University of Texas, Austin, TX 78712; Department of Computer Science, University of Wyoming, Laramie, WY 82071.
Brian A. Boyter , Laboratory of Image and Signal Analysis, University of Texas, Austin, TX 78712; Department of Electrical Engineering. United States Military Academy, West Point, NY 10996.
Chiun-Hong Chien , Laboratory for Image and Signal Analysis, University of Texas, Austin, TX 78712.
J. K. Aggarwal , Laboratory for Image and Signal Analysis, University of Texas, Austin, TX 78712.
With the advent of devices that can directly sense and determine the coordinates of points in space, the goal of constructing and recognizing descriptors of three-dimensional (3-D) objects is attracting the attention of many researchers in the image processing community. Unfortunately, the time required to fully sense a range image is large relative to the time required to sense an intensity image. Conversely, a single intensity image lacks the depth information required to construct 3-D object descriptors. This paper presents a method of combining the two sensory sources, intensity and range, such that the time required for range sensing is considerably reduced. The approach is to extract potential points of interest from the intensity image and then selectively sense range at these feature points. After the range information is known at these points, a graph structure representing the object in the scene is constructed. This structure is compared to the stored graph models using an algorithm for partial matching. The results of applying the method to both synthetic data and real intensity/range images are presented.
C. Chien, B. A. Boyter, J. K. Aggarwal and M. J. Magee, "Experiments in Intensity Guided Range Sensing Recognition of Three-Dimensional Objects," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 7, no. , pp. 629-637, 1985.