This work addresses the problem of synchronizing the sensors involved in the task of multiple object tracking (MOT) in Wireless Sensor Networks (WSN). We aim at reducing the overall in-network energy consumption along with bounding the uncertainty regarding targets' locations in WSN. Designing energy efficient scheduling mechanism is a challenge in WSN tracking scenarios due to the limitations on target's movement prediction, and lack of global network knowledge. The main observation of this work is that task conflicts and channel congestion preclude the utilization of the nodes shared by common tracking tasks, which may result in poor Quality of Tracking (QoT) and/or increasing target ambiguity. In order to tackle this problem, we propose a lightweight sensor scheduling policy - Synchronization based Sampling Reduction (SSR), which explicitly prunes the redundant measurements in the conflicting nodes without decreasing QoT, through synchronizing the tracking tasks. In addition to conserving the energy by reducing the samplings, SSR also is capable of mitigating the data associating problem in MOT, without requiring any global knowledge about the network. Our experiments demonstrate that SSR can significantly reduce the number of locations sampling, when compared to naïve approach that does not coordinate the nodes involved in multiple object tracking.