Task Specific Complexity Metrics For Electronic Vision

This paper presents a mathematical basis for establishing achievable performance levels for multisensor electronic vision systems. A random process model of the multisensor scene environment is developed. The concept of feature space and its importance in the context of this model is presented. A set of complexity metrics used to measure the difficulty of an electronic vision task in a given scene environment is developed and presented. These metrics are based on the feature space used for the electronic vision task and the a priori knowledge of scene truth. Several applications of complexity metrics to the analysis of electronic vision systems are proposed.