Unsupervised Semiconductor chamber matching based on shape comparison

Unsupervised thresholds for shape matching

Shape recognition systems usually order a fixed number of best matches to each query, but do not address or answer the two following questions: Is a query shape in a given database ? How can we be sure that a match is correct ? This communication deals with these two key points. A database being given, with each shape S and each distance δ, we associate its number of false alarms NFA(S, δ), nam...

Shape Matching Based on Invariants

Fast Musculoskeletal Registration Based on Shape Matching

This paper presents a new method for computing elastic and plastic deformations in the context of discrete deformable model-based registration. Internal forces are estimated by averaging local transforms between reference and current particle positions. Our technique can accommodate large non-linear deformations, and is unconditionally stable. Moreover, it is simple to implement and versatile. ...

Range Image Integration Based on 2D Shape Matching

This paper describes an integration technique of multiple range images. The range image integration is to estimate transfer parameters between two shape data, and it consists of an initial guess and a correction of the parameters. The initial guess process is based on 2D shape integration under a condition that the rotation axis of an object is parallel to one of sensor coordinate axes. After t...

Shape matching and retrieval based on multiple feature descriptors

A lot of 3D shape descriptors for 3D shape retrieval have been presented so far. This paper proposes a new mechanism, which employs several existing global and local 3D shape descriptors as input. With the sparse theory, some descriptors which play the most important role in measuring similarity between query model and the model in the dataset are selected automatically and an affinity matrix i...