Coverage quality and smoothness criteria for online view selection in a multi-camera network

Abstract

The problem of online selection of monocular view sequences for an arbitrary task in a calibrated multi-camera network is investigated. An objective function for the quality of a view sequence is derived from a novel task-oriented, model-based instantaneous coverage quality criterion and a criterion of the smoothness of view transitions over time. The former is quantified by a priori information about the camera system, environment, and task generally available in the target application class. The latter is derived from qualitative definitions of undesirable transition effects. A scalable online algorithm with robust suboptimal performance is presented based on this objective function. Experimental results demonstrate the performance of the method—and therefore the criteria—as well as its robustness to several identified sources of nonsmoothness.