Title :
Feature-utility measures for automatic vision programming
Author :
Chen, Chien-Huei ; Mulgaonkar, Prasanna G.
Author_Institution :
SRI Int., Menlo Park, CA, USA
Abstract :
Three utility measures that can be used to judge the effectiveness of features in a model-based matching strategy are defined: detectability, reliability, and error rate. With the probability framework, it is shown how it is possible to analytically estimate the reliability of a hypothesis using the measures of the individual features. Based on these measures, the authors have formulated and experimentally verified the matching cost (expressed as execution time) of locating an instance of a model in an image. An algorithm is presented for the selection of optimal seed features of the model using the estimated cost of criterion
Keywords :
computer vision; probability; automatic vision programming; detectability; error rate; feature-utility measures; matching cost; model-based matching strategy; optimal seed features; probability; reliability; Automatic programming; Construction industry; Costs; Feature extraction; Image recognition; Machine vision; Object recognition; Predictive models; Programming profession; Time measurement;
Conference_Titel :
Robotics and Automation, 1990. Proceedings., 1990 IEEE International Conference on
Conference_Location :
Cincinnati, OH
Print_ISBN :
0-8186-9061-5
DOI :
10.1109/ROBOT.1990.126276
