In order to compute camera viewpoints during sensor planning, Tarabanis et a1 present a group of feature detectability constraints which include six nonlinear inequalities in an eight-dimensional real space. It is difficult to compute robust viewpoints which satisfy all feature detectability Constraints. In this paper, the viewpoint setting is formulated as an unconstrainted optimization problem. Then a tree annealing algorithm, which is a general-purpose techniques for finding minima of functions of continuously-valued variables, is applied to solve this nonlinear multiconstraint optimization problem. Our results show that the technique is quite effective to get robust viewpoints even in the presence of considerable amounts of noise.
In addition, Yao and Allen REF , formulate the problem of sensor placement to satisfy feature detectability constraints as an unconstrained optimization problem, and apply tree-annealing to compute optimal camera viewpoints in the presence of noise.
Computing robust viewpoints with multi-constraints using tree annealing
1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century
1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century
Computer Science