106,293 research outputs found
IDSS: deformation invariant signatures for molecular shape comparison
<p>Abstract</p> <p>Background</p> <p>Many molecules of interest are flexible and undergo significant shape deformation as part of their function, but most existing methods of molecular shape comparison (MSC) treat them as rigid bodies, which may lead to incorrect measure of the shape similarity of flexible molecules.</p> <p>Results</p> <p>To address the issue we introduce a new shape descriptor, called Inner Distance Shape Signature (IDSS), for describing the 3D shapes of flexible molecules. The inner distance is defined as the length of the shortest path between landmark points within the molecular shape, and it reflects well the molecular structure and deformation without explicit decomposition. Our IDSS is stored as a histogram which is a probability distribution of inner distances between all sample point pairs on the molecular surface. We show that IDSS is insensitive to shape deformation of flexible molecules and more effective at capturing molecular structures than traditional shape descriptors. Our approach reduces the 3D shape comparison problem of flexible molecules to the comparison of IDSS histograms.</p> <p>Conclusion</p> <p>The proposed algorithm is robust and does not require any prior knowledge of the flexible regions. We demonstrate the effectiveness of IDSS within a molecular search engine application for a benchmark containing abundant conformational changes of molecules. Such comparisons in several thousands per second can be carried out. The presented IDSS method can be considered as an alternative and complementary tool for the existing methods for rigid MSC. The binary executable program for Windows platform and database are available from <url>https://engineering.purdue.edu/PRECISE/IDSS</url>.</p
Similarity measures for mid-surface quality evaluation
Mid-surface models are widely used in engineering analysis to simplify the analysis of thin-walled parts, but it can be difficult to ensure that the mid-surface model is representative of the solid part from which it was generated. This paper proposes two similarity measures that can be used to evaluate the quality of a mid-surface model by comparing it to a solid model of the same part. Two similarity measures are proposed; firstly a geometric similarity evaluation technique based on the Hausdorff distance and secondly a topological similarity evaluation method which uses geometry graph attributes as the basis for comparison. Both measures are able to provide local and global similarity evaluation for the models. The proposed methods have been implemented in a software demonstrator and tested on a selection of representative models. They have been found to be effective for identifying geometric and topological errors in mid-surface models and are applicable to a wide range of practical thin-walled designs
Shape mode analysis exposes movement patterns in biology: flagella and flatworms as case studies
We illustrate shape mode analysis as a simple, yet powerful technique to
concisely describe complex biological shapes and their dynamics. We
characterize undulatory bending waves of beating flagella and reconstruct a
limit cycle of flagellar oscillations, paying particular attention to the
periodicity of angular data. As a second example, we analyze non-convex
boundary outlines of gliding flatworms, which allows us to expose stereotypic
body postures that can be related to two different locomotion mechanisms.
Further, shape mode analysis based on principal component analysis allows to
discriminate different flatworm species, despite large motion-associated shape
variability. Thus, complex shape dynamics is characterized by a small number of
shape scores that change in time. We present this method using descriptive
examples, explaining abstract mathematics in a graphic way.Comment: 20 pages, 6 figures, accepted for publication in PLoS On
A Computational Model of the Short-Cut Rule for 2D Shape Decomposition
We propose a new 2D shape decomposition method based on the short-cut rule.
The short-cut rule originates from cognition research, and states that the
human visual system prefers to partition an object into parts using the
shortest possible cuts. We propose and implement a computational model for the
short-cut rule and apply it to the problem of shape decomposition. The model we
proposed generates a set of cut hypotheses passing through the points on the
silhouette which represent the negative minima of curvature. We then show that
most part-cut hypotheses can be eliminated by analysis of local properties of
each. Finally, the remaining hypotheses are evaluated in ascending length
order, which guarantees that of any pair of conflicting cuts only the shortest
will be accepted. We demonstrate that, compared with state-of-the-art shape
decomposition methods, the proposed approach achieves decomposition results
which better correspond to human intuition as revealed in psychological
experiments.Comment: 11 page
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Knowledge representation for basic visual categories
This paper reports work on a model of machine learning which is based on the psychological theory of prototypical concepts. This theory is that concepts learnt naturally from interaction with the environment (basic categories) are not structured or defined in logical terms but are clustered in accordance with their similarity to a central prototype, representing the "most typical'' member
Deformable Prototypes for Encoding Shape Categories in Image Databases
We describe a method for shape-based image database search that uses deformable prototypes to represent categories. Rather than directly comparing a candidate shape with all shape entries in the database, shapes are compared in terms of the types of nonrigid deformations (differences) that relate them to a small subset of representative prototypes. To solve the shape correspondence and alignment problem, we employ the technique of modal matching, an information-preserving shape decomposition for matching, describing, and comparing shapes despite sensor variations and nonrigid deformations. In modal matching, shape is decomposed into an ordered basis of orthogonal principal components. We demonstrate the utility of this approach for shape comparison in 2-D image databases.Office of Naval Research (Young Investigator Award N00014-06-1-0661
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