Several methods for 3D tracking use previous knowledge of scenario, which include workspace geometry, or active markers, that make feasible the tridimensional tracking of objects. However, in non-controllable scenarios there is a great challenge to guarantee a reliable and robust method. Parallel tracking method using PT-cameras are complicated because there are several conditions that affect motion detection (light, object displacement, PT-camera velocity, to mention a few). This work proposes a strategy for object tracking and estimating tridimensional position through camera-PT array. The camera array is used as a redundant way of focusing on reducing the error calculation. This method consists in simultaneously tracking the target object in all different cameras. Pan & Tilt are used as parameters of vectors in spherical coordinates. The tracking process is performed via active contours, which consists of a set of markers enclosing the target object and considering the contour as a high-energy zone. The tracking is then denoted as a Newton Rapson Optimization process which solves the problem of locating the maxima energy zone by superposing the latest reference position over the newest position in a given pair of images. Finally, our approach is tested in a controlled scenario. Luminance conditions are controlled and local references are used to match the estimated position and the real position.