Rotation invariant non-rigid shape matching in cluttered scenes

Abstract. This paper presents a novel and efficient method for locating deformable shapes in cluttered scenes. The shapes to be detected may undergo arbitrary translational and rotational changes, and they can be non-rigidly deformed, occluded and corrupted by clutters. All these problems make the accurate and robust shape matching very difficult. By using a new shape representation, which involves a powerful feature descriptor, the proposed method can overcome the above difficulties successfully, and it possesses the property of global optimality. The experiments on both synthetic and real data validated that the proposed algorithm is robust to various types of disturbances. It can robustly detect the desired shapes in complex and highly cluttered scenes.

• Type: Conference
• Year: 2010
• Where: ECCV
• Keywords: Cluttered Scenes, Computer Vision, Deformable Shapes, ECCV 2010, Powerful Feature Descriptor