For tracking infrared weak targets, a box particle labeled multi-bernoulli multi-target detection and tracking algorithm was proposed. To begin with, the algorithm uses the mean filter to denoise the grayscale image. Then, the region with higher intensity is selected as the interval measurement at current time by sorting the intensity of all the pixels. Finally, the box particle labeled multi-bernoulli filter is applied to tracking. Simulation are presented to demonstrate that the BOX-LMB-DT algorithm has stable and effective performance. In the same conditions, compared with the LMB particle filter under interval measurement, the operation efficiency of the BOX-LMB filtering is improved by 22.59% when the same tracking performance is achieved.