We present a method for supervised learning of shape descriptors for shape retrieval applications. Many contentbased shape retrieval approaches follow the bag-of-features (BoF) paradigm commonly used in text and image retrieval by first computing local shape descriptors, and then representing them in a ‘geometric dictionary’ using vector quantization. A major drawback of such approaches is that...

Shape is one of the primary features in Content Based Image Retrieval (CBIR). Many shape representations and retrieval methods exist. However, most of those methods either do not well capture shape features or are difficult to do normalization (or matching). Among them, methods based Fourier descriptors (FDs) achieve both good representation and easy normalization. FDs is often blamed for not b...

This paper presents the results of our research devoted to development of efficient methods for retrieval and indexing of documents with multimedia information that can help a business work smarter and gain an important advantage in whatever that business does. Particularly, a novel hybrid method for visual information retrieval (VIR) is proposed. It combines shape analysis of objects in image ...

We present a new benchmark for testing algorithms that create canonical forms for use in non-rigid 3D shape retrieval. We have combined two existing datasets to create a varied collection of models for testing. Canonical forms attempt to factor out a shape’s pose, giving a pose-neutral shape. This opens up the possibility of using methods originally designed for rigid retrieval for the task of ...

An one-line image database search method, which utilizes the boosted-shape feature similarities, is proposed. Salient common feature informations provided by the relevance feedback or multi-instance query are boosted for improving retrieval results. Weak classifiers are successively refined to yield a final strong classifier. The similarity between two shape samples was measured in statistic sp...

Shape retrieval and shape-based object recognition are closely related problems; however, they have di2erent task contexts, performance criteria, and database characteristics. In previous work, we proposed a method for similarity-based 2-D shape retrieval using scale-space part decompositions, part-frequency distributions, and structural indexing. In this paper, we evaluate the use of that shap...

Generic 3D shape retrieval is a fundamental research area in the field of content-based 3D model retrieval. The aim of this track is to measure and compare the performance of generic 3D shape retrieval methods implemented by different participants over the world. The track is based on a new generic 3D shape benchmark, which contains 1200 triangle meshes that are equally classified into 60 categ...

Memory is thought to be a constructive process in which the cortical regions associated with processing event features are reactivated during retrieval. Although there is evidence for non-detailed cortical reactivation during retrieval (e.g., memory for visual or auditory information reactivates the visual or auditory processing regions, respectively), there is limited evidence that memory can ...

For the year of past most three-dimensional objects are represented and mapped with spherical function. Since the mapping preserves important criteria such as geometrical information of a 3D object, the representation of a 3D shape in a suitable way is an important matter for 3D object retrieval. In many circumstances, spherical surface fitting to a 3D shape does not approximate very well, beca...

In earlier work, we developed a fast method for 2-D shape retrieval based on point correspondences of silhouette contours. That method did not assume that the database shapes had class labels. If class label information is added, then the shape retrieval system can be used for 2-D shape classification. This paper explores this application, by extending our prior shape retrieval method to make u...