3-D object recognition using adaptive scale MEGI

We propose a method for recognition of a 3-D object using a multi scale description of the object and adaptive matching. MEGI model is a description model to represent arbitrary shapes. However, many MEGI elements are necessary to represent uneven or carved surfaces with accuracy, so it is difficult to use them for recognition. As a solution, we make a tree which corresponds to the multi scale description of the object. While tracing the tree from the root which corresponds the coarsest representation to leaves, a matching algorithm presented in this paper assigns a different scale to each part of the object adaptively and estimates the matching score effectively.