Camera pose estimation across video sequences is an important issue under several computer vision applications. In previous work, the most popular approach consists on optimization techniques applied over 2D/3D point correspondences for two consecutive frames from a video sequence. Unfortunately, these optimization techniques are iterative and depend on nonlinear optimizations applied over some geometric constraint. For real-time embedded applications, another approach, more efficient in terms of computational size and cost, could be a linear or closed-form solution for the camera pose estimation problem. In this work, we introduce a new approach for camera pose estimation, this approach uses 2D visual features displacements as linear/dependent parameters for the camera pose estimation so, camera pose can be estimated without iterative behavior and without geometric constraints. As result, the proposed algorithm could be implemented inside a small FPGA device, suitable for smart cameras. Preliminary results are encourageous and show the viability of the proposed approach.