Continuous objects monitoring and tracking, which aims to detect the invasion of unauthorized materials of interest, is one of the most prominent applications in wireless sensor networks. In this paper, we propose a novel boundary recognition and tracking algorithm for continuous objects (BRTCO) to ensure the efficiency of objects contour extraction. On precondition of assuring the tracking accuracy, a collaborative filtering scheme is proposed to minimize the number of boundary nodes. Also, in the phase of data transmission, we take the advantage of clustering to ensure energy efficiency. A report node selection mechanism is designed based on the competition of cluster heads. Simulation results demonstrate that BRTCO can significantly reduce the total energy consumption, the number of boundary nodes, and the number of report nodes.