Existing visual servoing techniques which do not need metric information require, on the other hand, prior knowledge about the object's shape and/or the camera's motion. In this paper, we propose a new visual servoing technique which does not require any of them. The method is direct in the sense that: the intensity value of all pixels is used (i.e. we avoid the feature extraction step which introduces errors); and that the proposed control error as well as the control law are fully based on image data (i.e. metric measures are neither required nor estimated). Besides not relying on prior information, the scheme is robust to large errors in the camera's internal parameters. We provide the theoretical proofs that the proposed task function is locally isomorphic to the camera pose, that the approach is motion- and shape-independent, and also that the derived control law ensures local asymptotic stability. Furthermore, the proposed control error allows for simple, smooth, physically valid, singularity-free path planning, which leads to a large domain of convergence for the servoing. The approach is validated through various results using objects of different shapes, large initial displacements as well as large errors in the camera's internal parameters.