Particle tracking velocimetry methods (PTV) have a great potential to enhance the spatial resolution compared to spatial correlation-based methods (PIV). In addition, they are not biased due to inhomogeneous seeding concentration or in-plane and out-of-plane gradients so that the measurement precision can be increased as well. The possibility to simultaneously measure the velocity with the temperature, ph-value, or pressure of the flow at the particle location by means of fluorescent particles is another advantage of PTV. However, at high seeding concentrations, the reliable particle pairing is challenging, and the measurement precision decreases rapidly due to overlapping particle images and wrong particle image pairing. In this paper, it is shown that the particle image information acquired at four or more time steps greatly enhances a reliable particle pairing even at high seeding concentrations. Furthermore, it is shown that the accuracy and precision can be increased by using vector reallocation and displacement estimation using a fit of the trajectory in the case of curved particle paths. The improvements increase the PTV working range as reliable and accurate measurements become possible at seeding concentrations typically used for PIV measurements.