Content based 3D shape retrieval for broad domains like the World Wide Web has recently gained considerable attention in Computer Graphics community. One of the main challenges in this context is the mapping of 3D objects into compact canonical representations referred to as descriptors or feature vector, which serve as search keys during the retrieval process. The descriptors should have certa...

Many visual matching algorithms can be described in terms of the features and the inter-feature distance or metric. The most commonly used metric is the sum of squared differences (SSD), which is valid from a maximum likelihood perspective when the real noise distribution is Gaussian. However, we have found experimentally that the Gaussian noise distribution assumption is often invalid. This im...

We propose a novel Bayesian framework of symmetry-driven shape similarity to incorporate structural shape descriptor into conventional geometrical shape descriptor. We use rotation and reflection symmetries for structural shape description. Symmetry detection on each shape image provides a qualitative and a quantitative categorization of the types and the degrees of symmetry level. The posterio...

Generalising knowledge and matching patterns is a basic human trait in re-using past experiences. We often cluster (group) knowledge of similar attributes as a process of learning and or aid to manage the complexity and re-use of experiential knowledge [1, 2]. In conceptual design, an ill-defined shape may be recognised as more than one type. Resulting in shapes possibly being classified differ...

This paper introduces a novel 4D shape descriptor to match temporal surface sequences. A quantitative evaluation based on the Receiver-Operator Characteristic (ROC) curve is presented to compare the performance of conventional 3D shape descriptors with and without using a time filter. Featurebased 3D Shape Descriptors including Shape Distribution [24], Spin Image [14], Shape Histogram [1] and S...

We present a novel approach to measuring similarity between shapes and exploit it for object recognition. In our framework, the measurement of similarity is preceded by (1) solving for correspondences between points on the two shapes, (2) using the correspondences to estimate an aligning transform. In order to solve the correspondence problem, we attach a descriptor, the shape context, to each ...

A new method named Landmark Model Matching was recently proposed for fully automatic face recognition. It was inspired by Elastic Bunch Graph Matching and Active Shape Model. Landmark Model Matching consists of four phases: creation of the landmark distribution model, face finding, landmark finding, and recognition. A drawback in Landmark Model Matching is that, in the recognition phase, the we...

Shape context, a robust descriptor for point pattern matching, is applied in fingerprint matching by enhancing with minutiae type and angle details. A modified matching cost between shape contexts, by including the application specific contextual information, improves the accuracy of matching when compared with the original definition. To reduce computation for practical use, a simple pre-proce...

that have been already implemented in cultural heritage or we think are useful for the GRAVITATE project. These fields are relatively disjoint, and the research and development challenge of GRAVITATE is precisely to merge them. After the review of the current literature on these fields, we end the report with common remarks on possible or plausible crossconnections that suggest themselves. Thes...

in the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. to the best of our knowledge, the effect of noise factors on feature extraction has not been c...