Sparse features have been successfully used in shape retrieval, by encoding feature descriptors into global shape signatures. We investigate how sparse features based on saliency models affect retrieval and provide recommendations on good saliency models for shape retrieval. Our results show that randomly selecting points on the surface produces better retrieval performance than using any of th...

In this article, a fabulous method for database retrieval is proposed.  The multi-resolution modified wavelet transform for each of image is computed and the standard deviation and average are utilized as the textural features. Then, the proposed modified bit-based color histogram and edge detectors were utilized to define the high level features. A feedback-based dynamic weighting of shap...

Recent content-based similar shape retrieval techniques are mostly based on either the global invariant statistics derived from the entire shape or the primitive features computed from a shape's local regions. Global features are easy to compute but do not accurately reeect a real shape, hence, have a limited discrimination ability. On the contrary, primitive local features are computationally ...

An important problem in accessing and retrieving visual information is to provide efficient similarity matching in large databases. Though much work is being done on the investigation of suitable perceptual models and the automatic extraction of features, little attention is given to the combination of useful representations and similarity models with efficient index structures. In this paper w...

Efficient retrieval by content of visual information requires that visual content descriptors and similarity models are combined with efficient index structures. This problem is particularly challenging in the case of retrieval by shape similarity. The paper discusses retrieval by shape similarity, using local features and effective indexing. Shapes are partitioned into tokens following curvatu...

Most CBIR systems use low-level visual features for representation and retrieval of images. Generally such methods suffer from the problems of high-dimensionality leading to more computational time and inefficient indexing and retrieval performance. This paper focuses on a low-dimensional color and shape based indexing technique for achieving efficient and effective retrieval performance. We pr...

Similarity-based retrieval from databases of isolated visual shapes has become an important information retrieval problem. The goal of the current work is to achieve high retrieval speed with reasonable retrieval effectiveness, and support for partial and occluded shape queries. In the proposed method, histograms of local shape parts are coded as index vectors. To increase retrieval accuracy, a...

Sketch based 3D shape retrieval has become an important research topic in content based 3D object retrieval. To foster this research area, two Shape Retrieval Contest (SHREC) tracks on this topic have been organized by us in 2012 and 2013 based on a small scale and large scale benchmarks, respectively. Six and five (nine in total) distinct sketch based 3D shape retrieval methods have competed e...