Particle tracking is of fundamental importance in diverse quantitative analyses of dynamic intracellular processes using time-lapse microscopy. Due to frequent impracticability of tracking particles manually, a number of fully automated algorithms have been developed over past decades, carrying out the tracking task in two subsequent phases: (1) particle detection and (2) particle linking. An objective benchmark for assessing the performance of such algorithms was recently established by the Particle Tracking Challenge. Because its performance evaluation protocol finds correspondences between a reference and algorithm-generated tracking result at the level of individual tracks, the performance assessment strongly depends on the algorithm linking capabilities. In this paper, we propose a novel performance evaluation protocol based on a simplified version of the tracking accuracy measure employed in the Cell Tracking Challenge, which establishes the correspondences at the level of individual particle detections, thus allowing one to evaluate the performance of each of the two phases in an isolated, unbiased manner. By analyzing the tracking results of all 14 algorithms competing in the Particle Tracking Challenge using the proposed evaluation protocol, we reveal substantial changes in their detection and linking performance, yielding rankings different from those reported previously.