An efficient 3D object localization method using multiple cameras is provided. The proposed method comprises a three-dimensional object localization process that firstly generates a plurality of two-dimensional line samples originated from a pre-calibrated vanishing point in each camera view for representing foreground video objects, secondly constructs a plurality of three-dimensional line samples from the two-dimensional line samples in all the multiple camera views, and thirdly determines three-dimensional object locations by clustering the three-dimensional line samples into object groups.