An efficient algorithm is proposed for detecting vertical corner lines on buildings in quasi-Manhattan world scene. The vertical corner lines are useful geometric information of buildings in urban scene, whose importance is similar to that of corners on planar curves for various applications in computer vision. The algorithm employs a bottom-up and step-by-step pipeline processing procedure. First, straight-line segments are extracted as low-level features from the input building image by using a fast and accurate line segment detector. Secondly, the extracted straight-line segments are clustered to groups and associated to different vanishing points, which are computed by a J-Linkage estimator and act as the mid-level features. Finally, high-level features, vertical corner lines, are detected with several geometric constraints in quasi-Manhattan world. Experimental results demonstrate the efficiency of the new algorithm.