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Inspite extensive research on visual tracking of multiple people in computer vision area, the robustness and usability of visual trackers are still discouraging. Recently, a few laser-based detection and tracking methods have been developed in robotics area. However, poor features provided by laser data make the tracker fail in many situations. In this paper, we present a novel method that aims at reliably detecting and tracking multiple people in an open area. Multiple laser scanners and one camera are used as input sensors. In detection stage, laser-based detection algorithm captures newly appeared people and initializes the mean-shift-based visual tracker. In tracking stage, laser-based feet trajectory tracking result and visual body region tracking result are combined with a decision-level Bayesian fusion method. The experimental results demonstrate reliable and real-time performance of the method.