A new approach to 3D object recognition using multiple 2D camera views is proposed. The recognition system includes a turntable, a top camera, and a lateral camera. Objects are placed on the turntable for translation and rotation in the recognition process. 3D object recognition is accomplished by matching sequentially input 2D silhouette shape features against those of model shapes taken from a set of fixed camera views. This is made possible through the use of top-view shape centroids and principal axes for shape registration, as well as the use of a decision tree for feature comparison. The process is simple and efficient, involving no complicated 3D surface data computation and 3D object representation. The learning process can also be performed automatically. Good experimental results and fast recognition speed prove the feasibility of the proposed approach.