In this paper, a unified, segmentation-based approach is proposed to deal with both stereo reconstruction and moving objects detection problems using multiple stereo mosaics. Each set of parallel-perspective (pushbroom) stereo mosaics is generated from a video sequence captured by a single video camera. First a color-segmentation approach is used to extract the so-called natural matching primitives from a reference view of a pair of stereo mosaics to facilitate both 3D reconstruction of textureless urban scenes and man-made moving targets (e.g. vehicles). Multiple pairs of stereo mosaics are used to improve the accuracy and robustness in 3D recovery and occlusion handling. Moving targets are detected by inspecting their 3D anomalies, either violating the epipolar geometry of the pushbroom stereo or exhibiting abnormal 3D structure. Experimental results on both simulated and real video sequences are provided to show the effectiveness of our approach.