Bhandarkar, S.M., Parallelizing object recognition on the hypercube, Pattern Recognition Letters 13 (1992) 433-441. in this paper a parallel Interpretation Tree search algorithm for object recognition on the lntel iPSC/2 hypercube multicomputer is presented. The input to the algorithm is a set of sensory measurements consisting of sensor locations and the directions of the surface normal. Such data is typical of sparse range or tactile sensors. At this time the algorithm is capable of handling two-dimensional objects or three-dimensional objects located on a plane with all sensory measurements parallel to the plane. The objects are typically those which a robot would encounter in an industrial scene during the proces~ of automated inspection or automated assembly. The algorithm is able to handle polyhedra or objects which can be approximated as pieccwise combination of polyhedra. Both single- and multiple-object scenes are considered. Three strategies for mapping the Interpretation Tree search process on the hypercube are considered. The performance of the algorithm for each of these mapping strategies is examined in terms of parameters such as speed-up, processor utilization, inter-processor communication overhead and load sharing between processors. It is shown that the requirement for uniform load sharing leads to increased inler-proccssor communication. Experimental results are presented and fulnre directions are outlined.
['Suchendra M. Bhandarkar']
Parallelizing object recognition on the hypercube