Search results for "CBIR"
showing 9 items of 19 documents
Automatic image representation and clustering on mobile devices.
2010
In this paper a novel approach for the automatic representation of pictures on mobile devices is proposed. With the wide diffusion of mobile digital image acquisition devices, the need of managing a large number of digital images is quickly increasing. In fact the storage capacity of such devices allow users to store hundreds or even thousands, of pictures that, without a proper organization, become useless. Users may be interested in using (i.e., browsing, saving, printing and so on) a subset of stored data according to some particular picture properties. A content-based description of each picture is needed to perform on-board image indexing. In our work the images are analyzed and descri…
A novel approach to personal photo album representation and management
2008
In this paper we present a novel approach to personal photo album management allowing the end user to efficiently access the collection without any need for tedious manual annotation or indexing of the photos. The proposed work exploits methods and technology from the field of computer vision and pattern recognition for face detection, face representation and image annotation to automatically create description of images useful for content-based searching and retrieval. In fact, even if most of the used techniques are not reliable enough to address the general problem of content-based image retrieval, we show that, in a limited domain such as the one of personal photo album, it is possible …
Automatic Video Database Indexing and Retrieval
1997
The increasing development of advanced multimedia applications requires new technologies for organizing and retrieving by content databases of still digital images or digital video sequences. To this aim image and image sequence contents must be described and adequately coded. In this paper we describe a system allowing content-based annotation and querying in video databases. No user action is required during the database population step. The system automatically splits a video into a sequence of shots, extracts a few representative frames (said r-frames) from each shot and computes r-frame descriptors based on color, texture and motion. Queries based on one or more features are possible. …
Using Temporal Texture for Content-Based Video Retrieval
2000
Textures evolving over time are called temporal textures and are very common in everyday life. Examples are the smoke flowing or the wavy water of a river. The idea explored in this paper is that image features based on temporal texture could allow a better performance of current content-based video retrieval systems that are mainly based on static characteristics of representative frames, like color and texture. To this aim we analyze the spatio-temporal nature of texture and its application in content-based access to video databases. In particular, we represent temporal texture using the spatio-temporal autoregressive (STAR) model and a variation of self-organizing maps (SOM) where each n…
Unsupervised Clustering in Personal Photo Collections
2008
In this paper we propose a probabilistic approach for the automatic organization of collected pictures aiming at more effective representation in personal photo albums. Images are analyzed and described in two representation spaces, namely, faces and background. Faces are automatically detected, rectified and represented projecting the face itself in a common low dimensional eigenspace. Backgrounds are represented with low-level visual features based on RGB histogram and Gabor filter energy. Face and background information of each image in the collection is automatically organized by mean-shift clustering technique. Given the particular domain of personal photo libraries, where most of the …
Texture classification for content-based image retrieval
2002
An original approach to texture-based classification of regions, for image indexing and retrieval, is presented. The system addresses automatic macro-textured ROI detection, and classification: we focus our attention on those objects that can be characterized by a texture as a whole, like trees, flowers, walls, clouds, and so on. The proposed architecture is based on the computation of the /spl lambda/ vector from each selected region, and classification of this feature by means of a pool of suitably trained support vector machines (SVM). This approach is an extension of the one previously developed by some of the authors to classify image regions on the basis of the geometrical shape of th…
Unifying Textual and Visual Cues for Content-Based Image Retrieval on the World Wide Web
1999
A system is proposed that combines textual and visual statistics in a single index vector for content-based search of a WWW image database. Textual statistics are captured in vector form using latent semantic indexing based on text in the containing HTML document. Visual statistics are captured in vector form using color and orientation histograms. By using an integrated approach, it becomes possible to take advantage of possible statistical couplings between the content of the document (latent semantic content) and the contents of images (visual statistics). The combined approach allows improved performance in conducting content-based search. Search performance experiments are reported for…
Combining textual and visual cues for content-based image retrieval on the World Wide Web
2002
A system is proposed that combines textual and visual statistics in a single index vector for content-based search of a WWW image database. Textual statistics are captured in vector form using latent semantic indexing (LSI) based on text in the containing HTML document. Visual statistics are captured in vector form using color and orientation histograms. By using an integrated approach, it becomes possible to take advantage of possible statistical couplings between the content of the document (latent semantic content) and the contents of images (visual statistics). The combined approach allows improved performance in conducting content-based search. Search performance experiments are report…
Mean shift clustering for personal photo album organization
2008
In this paper we propose a probabilistic approach for the automatic organization of pictures in personal photo album. Images are analyzed in term of faces and low-level visual features of the background. The description of the background is based on RGB color histogram and on Gabor filter energy accounting for texture information. The face descriptor is obtained by projection of detected and rectified faces on a common low dimensional eigenspace. Vectors representing faces and background are clustered in an unsupervised fashion exploiting a mean shift clustering technique. We observed that, given the peculiarity of the domain of personal photo libraries where most of the pictures contain fa…