Julien Ricard

Generalizations of angular radial transform for 2D and 3D shape retrieval

The angular radial transform (ART) is a moment-based image description method adopted in MPEG-7 as a 2D region-based shape descriptor. This paper proposes generalizations of the ART to describe two-dimensional images and three-dimensional models. First, we propose an 2D extension, called GART, which allows applying ART to images while insuring robustness to all possible rotations and to perspective deformations. Then, we generalize the ART to index 3D models. This new 3D shape descriptor, so called 3D ART, has the same properties that the original transform: robustness to rotation, translation, noise and scaling while keeping a compact size and a good retrieval cost. The size of the descriptor is an essential evaluation parameter on which depends the response time of a content-based retrieval system. For both generalizations, many experiments were made on large databases and have shown, that GART outperforms ART in accuracy at the cost of speed, and that 3D ART outperforms the spherical harmonics shape descriptor (Vranic, D.V., Saupe, D., 2002. Description of 3D-shape using a complex function on the sphere, in: IEEE International Conference on Multimedia and Expo (ICME 2002), Lausanne, Switzerland, 2002, pp. 177-180; Funkhouser, T., Min, P. Kazhdan, M., Chen, J., Halderman, A., Dobkin, D., Jacobs, D., 2003. A search engine for 3D models. ACM Trans. Graphics 22(1), 83-105) in speed at the cost of accuracy.

Object of interest-based visual navigation, retrieval, and semantic content identification system

This study presents a content-based image retrieval system IMALBUM based on local region of interest called object of interest (OOI). Each segmented or user-selected OOI is indexed with new local adapted descriptors associated to color, texture, and shape features. This local approach is an efficient way to associate the local semantic content with low-level descriptors (color, texture, shape, etc.) computed on regions selected by the user. So the user actively takes part in the indexing process (offline) and can use a selected OOI as a query for the retrieval system (online). The IMALBUM system proposes original functionalities. A visual navigation tool allows to surf in the image database when the user has no precise idea of what he is really searching for in the database. Furthermore, when an OOI is selected as a query for retrieval, a semantic content identification tool indicates to the user the probable class of this unknown object. The performance of these different tools are evaluated on different databases.

ART extension for description, indexing and retrieval of 3D objects

This paper presents a new three-dimensional shape descriptor: 3D angular radial transform. It is an extension of the 2D region based shape descriptor proposed by MPEG-7, the angular radial transform (ART). We propose to generalize the ART to index 3D models.

Generalization of angular radial transform

Content based shape image retrieval is an important problem which gained the attention of the community. The challenge is to map the shape into compact and robust descriptor. This study presents a generalization of the angular radial transform (ART). The ART, recommended by the MPEG-7 standard, is only limited to binary images and is not robust to perspective deformations. We propose two generalizations of the ART allowing to apply it to color images and to make it robust to all possible rotations and to perspective deformations.

An Image Retrieval System Based on Local and Global Color Descriptions

This paper presents a new approach for visual-based image retrieval method with respect to the MPEG-7 still image description scheme. A segmentation method based on a multivariate minimum cross entropy is used hierarchically for partitioning the color image in classes and regions. Local and global descriptors are defined in order to characterize the color feature of these regions. The local descriptors provide information about the local activity in the image, and the global ones evaluate the qualitative image content. Their combination increases significantly the performances of the image retrieval system IMALBUM presented in this paper. The retrieved images are presented in a description space allowing the user to better understand and interact with the search engine results.

Multi-component cross entropy segmentation for color image retrieval

This paper presents an adaptive color image segmentation method based on cross entropy minimization. This method is a multi-component approach and provides a hierarchical partitioning of the 3D color space using spherical neighbourhoods. The number of dominant colors (classes) issued from this segmentation is automatically estimated. This avoids an a priori estimation of the number of final classes. The segmentation method is then applied for image retrieval purposes. Local and global descriptors are defined in order to characterize the color feature of these classes. The local descriptors provide information about the local activity in the image class per class, and the global ones evaluate the qualitative image content. Their combination increases significantly the performance of the image retrieval system presented in this paper.

An objective performance evaluation tool for color based image retrieval systems

This study addresses the problem of the objective performance evaluation of image retrieval systems. Considering the color feature, a tool for synthetic image databases generation is proposed. This allows to control the number and location of the dominant colors in the Lab space and provides also their spatial coherency. It is then possible to sort exactly the images for the color feature. We also propose a new similarity measure to compare images described by the color feature. Based on the assumption of a Gaussian distribution for each dominant color, each image is modeled by the sum of these Gaussian distributions. The similarity measure performs a Kullmans distance between two modeled distributions. The objective performance evaluation based on the synthetic database is done for comparing our image retrieval system (IMALBUM) which uses the new similarity measure and MPEG7 approach. Experiments on MPEG7 database are also presented as a subjective evaluation and discussed.