In this paper, we consider multi-sensor with partly overlapping field of view (FoV) in the labeled random finite set (L-RFS) framework. This is different from most existing multi-sensor tracking algorithms, where the sensors are assumed to have the same FoV. We describe the partly overlapping FoV by modeling probability field of detection (PFoD) for individual sensors in whole observation area and can be seen as the same range of FoV. We consider all these using generalized labeled multi-Bernoulli (GLMB) filter in labeled RFS framework. Besides, a multi-sensor measurement driven of birth model is proposed. Finally, the effectiveness of the proposed algorithm is verified by experiments.